SYSTEMS AND METHODS FOR ENHANCED NATURAL HYDROGEN EXPLORATION

Description

FIELD OF THE DISCLOSURE

The present disclosure relates generally to hydrogen resources and, more particularly, to systems and methods for enhanced natural hydrogen exploration using fault data.

BACKGROUND OF THE DISCLOSURE

As concerns over climate change continue to increase, there is growing interest in mitigating the effects of industrial processes, such as cement and steel production, and combustion processes utilizing fossil fuels. Hydrogen-based energy is one approach that has been suggested for mitigating the effects of carbon dioxide and other greenhouse gases. Hydrogen-based energy is carbon free. Thus, hydrogen-based industrial operation may emit fewer greenhouse gases (CHGs) by mitigating the presence of carbon during industrial procedures. Ideally, formations targeted for hydrogen processing operations are effective to collect hydrogen in a manner that is economically efficient and environmentally sound. However, typical hydrogen reservoirs are expensive to access and environmentally costly to produce.

Although current techniques for producing hydrogen energy, and for hydrogen exploration in particular, are based on technological advancements made over many years, current hydrogen exploration technology may still be ineffective to achieve ideal hydrogen production results. For example, hydrogen production in a typical formation may be expensive and environmentally tenuous. As a result, implementation of hydrogen exploration technologies may be hindered, consequently reducing CGH mitigation. Accordingly, there is an impetus to improve current hydrogen exploration technology to improve the cost and environmental impact of hydrogen production, including, for example: reducing the environmental impact of hydrogen exploration procedures, increasing the efficiency in a variety of target hydrogen production formations, increasing the throughput of hydrogen production, decreasing the cost of hydrogen production, improving the characterization of a target formation for optimal hydrogen exploration, reducing the cost and inefficiency associated with hydrogen exploration, and the like.

Consequently, there exists a need for further improvements in hydrogen exploration technology to overcome the aforementioned technical challenges and other challenges not mentioned.

SUMMARY OF THE DISCLOSURE

Various details of the present disclosure are hereinafter summarized to provide a basic understanding. This summary is not an exhaustive overview of the disclosure and is neither intended to identify certain elements of the disclosure, nor to delineate the scope thereof. Rather, the primary purpose of this summary is to present some concepts of the disclosure in a simplified form prior to the more detailed description that is presented hereinafter.

According to an embodiment consistent with the present disclosure, a method for hydrogen exploration may include one or more steps. The method may include obtaining one or more hydrogen prospects, the one or more hydrogen prospects selected based on one or more parameters; The method may include constructing one or more fracture networks based on the one or more hydrogen prospects, the one or more fracture networks each having a source rock area value. The method may include, based on the source rock area value for each of the one or more hydrogen prospects, generating a source rock exposure value for each of the one or more prospects. The method may include outputting a production prediction based on the source rock exposure value for each of the one or more hydrogen prospects.

In another embodiment, a system for hydrogen exploration may include a memory and one or more processors. In one example, the one or more processors configured to cause the apparatus to perform one or more steps. The one or more steps may include obtaining one or more hydrogen prospects, the one or more hydrogen prospects selected based on one or more parameters. The one or more steps may include constructing one or more fracture networks based on the one or more hydrogen prospects, the one or more fracture networks each having a source rock area value. The one or more steps may include, based on the source rock area value for each of the one or more hydrogen prospects, generating a source rock exposure value for each of the one or more prospects. The one or more steps may include outputting a production prediction based on the source rock exposure value for each of the one or more hydrogen prospects.

Any combinations of the various embodiments and implementations disclosed herein can be used in a further embodiment, consistent with the disclosure. These and other aspects and features can be appreciated from the following description of certain embodiments presented herein in accordance with the disclosure and the accompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic view of an example geological hydrogen resource formation having features associated with hydrogen recovery.

FIG. 2 is a cross-sectional view of an example geological hydrogen resource formation having features associated with hydrogen recovery.

FIG. 3 is an example graph illustrating serpentinization factors for peridotite and pyroxenite.

FIG. 4 is an example graph illustrating temperature and thermal conductivity for a hydrogen-bearing formation.

FIG. 5 illustrates an example phase diagram for a hydrogen-bearing formation.

FIG. 6 illustrates an example flow diagram of a method for predicting natural hydrogen production using fault parameters data, according to aspects of the present disclosure.

FIG. 7 illustrates an example flow diagram of a method for predicting natural hydrogen production using fault parameters data, according to aspects of the present disclosure.

FIG. 8 depicts an example fluid flow localized within a narrow fault zone, according to aspects of the present disclosure.

FIG. 9 depicts an example fault zone that is connected to a fracture network on one side of the fault, according to aspects of the present disclosure.

FIG. 10 illustrates example of earthquake data, according to aspects of the present disclosure.

FIG. 11 illustrates a cross-section showing a fault area and the values that are used to compute the seismic moment.

FIG. 12 illustrates an example relationship between earthquake magnitude, moment (energy release), slip magnitude, and fault size.

FIG. 13 illustrates a histogram of fault lengths (Lf) derived from a set of example datasets.

FIG. 14 illustrates an example relationship between strike-slip earthquake data and seismic moment.

FIG. 15 illustrates an example cumulative number of earthquakes as a function of earthquake magnitude.

FIG. 16 depicts a histogram of the earthquake data of FIG. 15.

FIG. 17 illustrates a discrete fracture network representation of resolved active faults represented as equivalent area representations, according to aspects of the present disclosure.

FIG. 18 illustrates a discrete fracture network representation of resolved active faults represented as equivalent volume representations, according to aspects of the present disclosure.

FIG. 19 illustrates an example concept for natural hydrogen production in faulted basement source rock, according to aspects of the present disclosure.

FIG. 20 illustrates a computer system which may be implemented as part of at least one embodiment of the present disclosure.

FIG. 21 is an example of a block diagram of a system described herein in accordance with certain embodiments.

FIG. 22 is a block diagram of a computer system that may be used to implement one or more of the systems or methods described herein in accordance with certain embodiments.

FIG. 23 depicts a cloud computing environment that can be used to perform one or more actions according to an aspect of the present disclosure.

DETAILED DESCRIPTION

Embodiments of the present disclosure will now be described in detail with reference to the accompanying drawing figures. Like elements in the various figures may be denoted by like reference numerals. Further, in the following detailed description, specific details are set forth in order to provide a more thorough understanding of the claimed subject matter. However, it will be apparent to one of ordinary skill in the art that the embodiments disclosed herein may be practiced without these specific details, or with details that are not described herein in the interest of clarity. Thus in some instances, well-known features have not been described in detail to avoid unnecessarily complicating the description. Additionally, it will be apparent to one of ordinary skill in the art that the scale of the elements presented in the accompanying drawing figures may vary without departing from the scope of the present disclosure.

Aspects of the present disclosure provide systems and methods for natural hydrogen exploration using fault data to identify favorable exploration targets. A natural hydrogen system is one in which component reagents for generated hydrogen may be derived from features within natural geological formations (e.g., rock formations). In certain aspects, the reactions may occur in place, whether at a certain depth within a formation or near the surface of a formation. In at least one embodiment, methods described herein may be applied during hydrogen production that targets direct production from the host rocks (e.g., white hydrogen or gold hydrogen). In at least one embodiment, methods described herein may be applied with assistance via a stimulant (e.g., orange hydrogen). Faults, fault-related fracture zones, as well as fracture zones not directly formed by faulting but affected by subsequent fault activity (henceforth all referred to as “faults” below for brevity) may serve as migration pathways in a tight source formation that would otherwise have low permeability. Faults can be sealing (e.g., cemented) or flow-enhancing. In at least one embodiment, active faulting may be identified as an agent for circulating water (e.g., natural water or injected water) that may facilitate hydrogen reactions. Active faulting may also be identified as a set of conduits for hydrogen migration towards a trap or a producer well. Active fault identification may be especially important for identifying subsurface fluid migration because, unlike sedimentary rock formations targeted for petroleum production, hydrogen source rocks may be crystalline and may have little intrinsic porosity and permeability that would allow fluid migration without fracture.

Earthquakes may be direct indicators of active faulting in recent geologic history. Earthquake data may be useful to screen for geological zones able to produce natural hydrogen. Methods provided herein may facilitate analysis of a geological fault population using earthquake data to determine conditions conducive to active flow. Methods provided herein may further allow analysis of natural hydrogen productivity potential due to geochemical hydration reactions. In many cases, hydrogen may be generated from pre-existing hydration of several source rocks within a formation. An example source rock may include a source rock containing Fe-rich (particularly Fe²⁺) minerals (e.g., olivine, pyroxene, spinel, mica, illite, chlorite, smectite, etc.), serpentinite, kimberlite, peridotite, pyroxenite, basalt/diabase, gabbro, granite (sensu lato), clay-rich sedimentary rock and rock assemblages collectively referred to as ophiolites. Ophiolites, for example, are commonly referenced in natural hydrogen literature because of the well-known hydration reaction called serpentinization. A hydration reaction requires the source rock to receive an influx of water. In many cases, water may be derived from the ocean, groundwater, modern aquifers that recharge from rainwater, from deep-seated paleo-aquifers, from injected water during engineering operations, and the like. In the hydrogen systems framework that is presented according to aspects of the present disclosure, active faults and associated fractures may serve as a conduit for water influx as well as a pathway for enhanced migration of generated hydrogen. Accordingly, the hydration reactions may only occur in certain geological locations and under favorable reaction conditions. Systems and methods provided herein may utilize fault data to identify natural hydrogen systems that occur under favorable conditions, and to predict corresponding hydrogen generation.

Example Hydrogen Production

FIGS. 1 and 2 illustrate example formations that may be targets for hydrogen production. FIG. 1 illustrates a schematic view of an example formation for natural hydrogen exploration. In FIG. 1, point 1 is a radiolysis reaction, point 2 is a serpentinization reaction, point 3 is a deep-seated fault, point 4 is a set of seeps, point 5 is a microbial consumption point, point 6 is a set of abiotic reactions, point 7 is production from a set of traps, point 8 is a direct natural hydrogen drilling, and point 9 is an enhanced hydrogen stimulation plant. FIG. 2 illustrates a schematic view of an example formation for natural hydrogen exploration.

The formation of FIG. 2 relies on faults 102 to transport hydrogen from a deep serpentinized source rock 106. Fault zones 102 and associated fractures in hydrogen source rocks 104 may be associated with natural hydrogen. Faults 102 and associated fractures may function as conduits that enhance fluid flow at the subsurface. In some cases, fault zone 102 presence has been correlated with oil and gas anomalies. In FIGS. 1 and 2, water infiltration into iron-rich mantle rock 106, or to the source rock serpentinization zone 206 may be assumed but may not be constrained. Faults 102 may enhance fluid migration into the source rock 106/206 and may facilitate gas migration to traps that are disposed above the source rock 106/206. As depicted in FIG. 1, natural hydrogen may be produced in situ by direct drilling and production, or by using enhanced methods such as circulating water through a pair of injector-producer wellbores. However, even under enhanced conditions, the tight nature of the source rocks 106/206 may suggest the presence of fault enhanced migration pathways. In some cases, there may be a correlation with a deep fault zone and natural hydrogen concentration at the surface. Similarly, there may be a correlation between natural hydrogen concentration and fracture systems in certain ophiolites. Additionally, active fault zones may control fluid migration between deep source rocks and outlets at the surface.

In the process of natural hydrogen generation, a hydration reaction may occur in iron bearing rocks. The hydrogen reaction may be caused by circulation of ground water or aquifer sources. In some cases, the reaction may be represented by the simplified equation as follows:

In (1), the original rock may contain iron (II) or Fe²⁺. As this iron comes into contact with water, it oxidizes and becomes iron (III) or Fe³⁺ in the resultant rock. The hydrogen in the water (left side of equation) may simultaneously become reduced to free H₂ (right side of equation). Iron (II) is the dominant driving force of this hydration reaction, and may facilitate hydrogen generation.

The compositional elements of the hydration reactions may be characteristics of a type of source rock. Embodiments of the present disclosure are described in terms of serpentinization of olivine bearing rocks such as peridotite, gabbro, and basalt, or as an assemblage of these rocks (termed ‘ophiolite’). However, it is noted that other relevant hydration reactions are possible. The mineral olivine may be formed in a solid-solution and can have large variations in chemical composition, ranging between an Mg-rich and an Fe-rich endmember. Because composition of olivine can vary, the stoichiometry of equation (1) may vary. An example reaction equation for serpentinization is provided as follows:

The product of mixing water with olivine (left side of equation 2) is serpentine, magnetite, brucite, and hydrogen (right side of equation 2). The chemical reaction that produces natural hydrogen may depend on at least one of the chemical composition of the rock, access to a water source, chemical composition of the water. The chemical reaction may occur within an optimal temperature range of about 160° C. or more to about 450° C., such as about 210° C. or more to about 400° C. or less, such as about 300° C. An example of the modeled reaction is illustrated in FIG. 3 comparing compositional variations between peridotite 302 and pyroxenite 304 source rocks. Specifically, FIG. 3 illustrates a predicted equilibrium of hydrogen concentrations for serpentinization of lithologies having distinct olivine to orthopyroxene mass ratios as a function of temperature.

In some cases, hydrogen can be generated by hydration reactions in banded iron formations. Banded iron formations (BIFs) are massive chemical deposits composed of alternating layers of chert and iron-rich minerals (e.g., hematite, magnetite, and siderite). An intermediate reaction of iron (II) and water in banded iron formations is provided for ferric oxides (e.g., hematite and magnetite) and iron carbonate (e.g., siderite) BIFs and may yield free hydrogen as follows:

The temperature ranges may define the depths at which the reactions may occur, which may be determined by the thermal gradient, a function of the thermal conductivity of the rock and regional heat flow data. Rocks containing radioactive materials that are undergoing radioactive decay may have higher thermal conductivity. Rocks adjacent to magmatic sources such as volcanic intrusions may have higher heat flow. An example of temperature information acquired from wellbore data is illustrated in FIG. 4. Specifically, FIG. 4 illustrates temperature and thermal conductivity in well 402 and well 404. The lines 406 represent thermal conductivity, black circles 408 are corrected bottom hole temperature readings, and the black lines 410 are a continuous temperature values.

For oceanic settings such as mid-ocean ridges, the presence of ultramafic rock combined with high heat flow and constant water supply may provide suitable conditions for serpentinization reactions. For onshore conditions, the appropriate source rock types may occur at the surface or at depth, which may be determined from well bore data (e.g., wireline logs, core, drilling data) or geophysical data (e.g., seismic, gravity, and magnetic data). For onshore conditions with low geothermal gradients, the reaction temperatures may be unlikely to occur at the surface or at shallow depths (e.g., as shown in FIG. 2). However, some onshore geologic locations may have higher geothermal gradients leading to higher temperatures encountered at shallower depths. Hydration reactions in hydrogen source rocks will have their own kinetic characteristics whereby generation rates are controlled by pressure and temperature. For example, in a common example of a serpentinite formation, temperature dependence may be significant while pressure dependence may be negligible for the main structural types (e.g., lizardite, chrysotile, polygonal serpentine, and antigorite), as illustrated in the example phase diagram of FIG. 5. FIG. 5 specifically illustrates a phase diagram having hydrogen generating reactions on the left side, at temperatures less than about 450° C., such as about 400° C. Sub-vertical phase transition boundaries may indicate minimal pressure dependence. A may represent antigorite. B may represent brucite. C may represent chlorite. Chr may represent chrysostile. L may represent lizardite. F may represent forsterite. T may represent talc, and W may represent water.

Aspects Related to Natural Hydrogen Exploration Using Fault Data

Aspects of the present disclosure provide methods and systems for utilizing earthquake data from seismic data repositories to determine active hydrogen resources. In at least one embodiment, methods described herein may utilize properties of faults within active seismic zones to estimate natural hydrogen generation potential resulting from water-rock interactions. The methods presented herein may assume hydrogen generation by hydration reactions related to Fe-bearing (ferrous) source rocks. In at least one embodiment, the natural hydrogen generation potential may represent a production prediction for use in hydrogen resource exploitation, either from natural hydrogen or from stimulated hydrogen production. The production prediction estimate described in at least one embodiment may be used in decisions regarding field development and may be used to define various specifications for the field operations associated with hydrogen extraction. In at least one embodiment, the production prediction may be a volume value (e.g., a static value) or a flux value (e.g., a dynamic value) of hydrogen resulting from natural generation as described below.

FIG. 6 illustrates an example flow diagram of a method for predicting natural hydrogen production using fault parameters data, which may be performed according to at least one embodiment of the present disclosure. The one or more blocks of FIG. 6 may be performed by a computer system or device (e.g., the computer systems and devices described below with respect to FIGS. 20-23), including by a computer processor and a network communication interface. At step 602, the system or device obtains one or more hydrogen prospects, the one or more hydrogen prospects selected based on one or more parameters. In at least one embodiment, the one or more hydrogen prospects are selected based on at least one of rock characteristics of the one or more hydrogen prospects, fault characteristics of the one or more hydrogen prospects, and earthquake catalog data of the one or more hydrogen prospects. In at least one embodiment, the one or more hydrogen prospects represent fractured subsurface reservoirs connected to active fault systems.

At step 604, the system or device construct one or more fracture networks based on the one or more hydrogen prospects, the one or more fracture networks each having source rock area value. In at least one embodiment, constructing the one or more fracture networks based on the one or more hydrogen prospects includes defining a set of subsurface fault parameters for each of the one or more hydrogen prospects, the set of subsurface fault parameters characterizing an active seismic zone, and delineating, based on a comparison of the set of subsurface fault parameters and the active seismic zone, an active fault volume. In at least one embodiment, constructing the one or more fracture networks based on the one or more hydrogen prospects includes identifying a set of connections between the active fault volume and at least one water source, and identifying, based on the set of connections, water source flux. In at least one embodiment, constructing the one or more fracture networks based on the one or more hydrogen prospects includes forming a source rock exposure surface, and generating an area of the source rock exposure surface based on a framework model of the active fault volume. In at least one embodiment, forming the source rock exposure surface includes comparing the active fault volume to a source rock volume, and identifying exposure points on the active fault volume to generate the source rock exposure surface. In at least one embodiment, the framework model is generated using at least a statistical distribution of earthquakes. In at least one embodiment, the framework model is generated using a discrete fracture network (DFN) model. In at least one embodiment, the DFN model is constructed based on geological data. In at least one embodiment, the framework model is generated using equivalent volume data.

At step 606, the system or device, based on the source rock area for each of the one or more hydrogen prospects, generates a source rock exposure value for each of the one or more prospects. At step 608, the system or device outputs a production prediction based on the source rock exposure value for each of the one or more hydrogen prospects. In at least one embodiment, the production prediction estimates a natural hydrogen gas volume accumulated in the one or more hydrogen prospects. In at least one embodiment, outputting a production prediction based on the source rock exposure value for each of the one or more hydrogen prospects includes calculating the production prediction based on at least one of the area of the source rock exposure surface and the water source flux. In an optional step, the system or device may extract, based on the production prediction, natural hydrogen from a fractured subsurface reservoir represented by at least one of the one or more hydrogen prospects.

FIG. 7 illustrates an example flow diagram of a method for predicting natural hydrogen production using fault parameters data, which may be performed according to at least one embodiment of the present disclosure. The one or more blocks of FIG. 7 may be performed by a computer system or device (e.g., the computer systems and devices described below with respect to FIGS. 20-23), including by a computer processor and a network communication interface. At step 702, a system or device performs a regional exploration screening for natural hydrogen play potential using geological maps, source rock data, regional fault maps, and other relevant screening data. At step 704, the system or device estimates the preliminary hydrogen production potential using analog data or analytical calculations. At step 706, the system or device uses the estimations of step 704 to determine if the potential hydrogen play may warrant further study. At step 708, the system or device reads a set of subsurface fault parameters characterizing an active seismic zone and delineates an active fault volume based on the subsurface fault parameters relationship with the active seismic zone. At step 710, the system or device determines whether the active fault volume connects to a water source to access a water source flux, and to determine if the active fault volume is exposed to a source rock to form a source rock exposure.

At step 712, the system or device calculates the hydrogen generation potential for a field scenario. In at least one embodiment, an accurate calculation may be generated by computing the total surface area of the source rock that is exposed to water over time in order to solve the hydrothermal hydration reaction described above. The total surface area may be derived from framework models of the fault network via at least one of the following: (1) Using the statistical distribution combining the theoretical magnitude to length relationship (e.g., as described with respect to FIG. 12) and real data (e.g., as described with respect to FIG. 16); (2) Building a discrete fracture network (DFN) model conditioned to the minimum available geologic data (e.g., as described with respect to FIG. 17); (3) Building a DFN model conditioned to more robust geological data by combining FIG. 17 with geologic descriptions such as those describe with respect to FIGS. 8 and 9, which may be derived from maps, three-dimensional (3D) seismic data, well data, and the like; (4) Building an equivalent volume data that incorporates a natural fracture network based on other forms of fault (e.g., side-wall leak-off, finite width fault core, fault splays, finite width damage zone) comprising an equivalent reaction zone (e.g., as described with respect to FIG. 18). Where available, supporting information from microseismic monitoring may be used to further constrain the predicted extent of faults at the depth of interest and in contact with source rock interval. Using one of the above derivation methods (1)-(4) may allow for constrained reaction predictions.

At step 714, the system or device calculates a production prediction of the natural hydrogen gas accumulated in a subsurface reservoir connected to the active fault volume based on the area of the source rock exposure and on the water source flux. In at least one embodiment, the computed hydrogen productivity in the cumulative equivalent area (e.g., as described with respect to FIG. 17) or cumulative equivalent volume (e.g., as described with respect to FIG. 18) may be determined using reaction equations such as equations (1)-(5). In one non-limiting example, the curves illustrated in FIG. 3 may show hydrogen generation in mmol/kg, and may be predicted using computer modeling techniques and adapted and scaled for large reaction volumes. In at least one embodiment, the chemical reactions may be solved computationally and linked to dynamic flow construction modules. In at least one embodiment, the reactions and fluid flux may be computed independently and passed as input/output values. In at least one embodiment, the reactions may be determined from laboratory tests and treated empirically. In at least one embodiment, the essential workflow includes determination of the surface area of active faults, which may be represented as cumulative equivalent area or cumulative equivalent volume, and then to solve the hydration reactions given the hydrothermal environmental conditions. A simplified version of this reaction concept may be depicted and described with respect to FIG. 19.

FIGS. 8 and 9 are example models of natural hydrogen reservoirs occurring in active seismic zones. Such hydrogen reservoirs may be targeted in the method of FIG. 7. FIGS. 8 and 9 illustrate the relationship between active faults, inactive faults, water circulation, ultramafic source rocks, serpentinization reactions, and hydrogen migration paths. In the scenarios presented in FIGS. 8 and 9, the cause of the earthquakes may be unknown. However, active portions of the fault zone resulting from the earthquake may preferentially intake a higher volume of water than impermeable or low permeability host rock that may surround the fault zone. FIG. 8 depicts an example fluid flow localized within a narrow fault zone. Water-rock interactions may be limited to a narrow zone surrounding the main fault. Water may enter the fault zone by deep connectivity with one of the following (a) meteoric water at the ground surface; (b) present day buried aquifer; (c) a paleo-aquifer that collected water during a previous geologic period including but not limited to periods of glacial melting. FIG. 9 depicts a similar example fault zone that is connected to a fracture network on one side of the fault. Activation of the fault zone may allow a greater-than-average volume of water to enter the host rock volume through connected fracture flow. FIG. 8 reflects a minimum volume scenario. FIG. 9 reflects a moderate volume scenario based on asymmetric fracture connectivity. Other scenarios may be envisioned with different patterns of fault and fracture connectivity, according to certain aspects of the present disclosure.

In some cases, water source flux may be present if the fault zone penetrates a known source of water (e.g., an aquifer at a certain stratigraphic depth, ground water when a fault extends to the surface). In at least one embodiment of the present disclosure, a water source is at or near the surface, the presence and amount of water flux may be determined using ground water recharge data such as information about rainfall or other hydrogeologic data. Source rock exposure is present if the fault zone penetrates the source rock geological formation as presented in FIGS. 1 and 2. The source rock exposure may be defined on the structural rupture area of the active faults.

In at least one embodiment, earthquake data may be incorporated into systems and methods described herein to provide information on the location, depth, and frequency of active faulting. Enhanced water circulation may be present in seismogenic terranes hydraulically connecting rocks from basement to surface along active fault zones. Earthquake data may be historic and/or real-time earthquake data. An example of earthquake data is shown in FIG. 10. The data may contain dates, times, geospatial coordinates, estimated depth(s) (shown in km), event magnitude, other seismological attributes, or some combination therein. Some events, such as the event 1002 in FIG. 10, include strike information of the activated fault plane and dip information of the activated fault plane (e.g., depicted as ‘beachball’ plot 1004). In some cases, earthquake data may indicate that earthquake magnitude is related to fault size. For example, as illustrated in FIG. 11, the rupture area may reflect a portion of the total fault surface given length, L, and width, W, that slips by some distance, D. FIG. 11 illustrates a cross-section showing a fault area and the values that are used to compute the seismic moment. In some examples, fault patch may slip according to a non-linear slip distribution and may have an irregular shape. In such non-linear cases, the size of the fault as defined by a maximum length dimension may be approximated by assuming a square, circular, or elliptical patch size.

FIG. 12 illustrates an example relationship between earthquake magnitude, moment (energy release), slip magnitude, and fault size. In one example, the black line 1202 highlights an example fault of magnitude 4 with several centimeters of slip on a fault having a length of about 0.5 km or more to about 4.5 km or less (e.g., about 1 km to about 4 km). The relationships illustrated in FIG. 12 may provide estimation parameters for upper and lower bounds of the size of a given fault using earthquake magnitude data. Accordingly, using a larger population of earthquakes, it may be possible to collect statistical information on the range of earthquake magnitudes and corresponding fault lengths. In one example, a map-based method for linking mapped fault lengths with potential earthquake magnitude may be utilized to compute earthquake magnitudes derived from surface fault lengths (FLEM) as follows:

FLEM = M = a + b · log ⁢ ( L f ) , ( 6 )

• • where a and b are constants related to fault kinematics. FIG. 13 illustrates a histogram of fault lengths (L_f) derived from a set of example datasets. Inset shows the same histogram for fault lengths greater than or equal to about 45 km.

In some cases, pre-existing and verified empirical relationships may also be used to compute fault area from an earthquake catalog data. For example, FIG. 14 illustrates an example relationship between strike-slip earthquake data and seismic moment. In at least one embodiment, the cumulative fault length or area for active faults can therefore be constrained using statistical information from earthquake data, like the information from FIG. 14. In at least one embodiment, mechanical models may also be utilized to validate assumptions about active fault trends or seismogenic locations. For example, fault and fracture stability computations may be employed to understand the relationship between tectonic stresses, faults, and borehole data in a variety of hydrogen formations. In at least one embodiment, if map data is available, cumulative fault length (or area) may be compared to ensure an active fault length for a region is less than the total mapped faults. In at least one embodiment, fault area may be computed by assuming a height to length ratio for rectangular or square fault patches or using a circular or elliptical fault patch shape assumption.

In some cases, fault statistics may be obtained from earthquake catalog data. Example catalog data is shown in FIGS. 15 and 16. FIG. 15 shows an example cumulative number of earthquakes as a function of earthquake magnitude. The magnitude of completeness Mc (e.g., about 2.70) for this data set may indicate the minimum earthquake size that is accurately detected by the seismic monitoring network. Line 1502 marking the slope of the curve reflects the b-value (e.g., about 0.94±0.05), which is a calculation of the scaling ratio between small and large earthquakes. In at least one embodiment, using the relationships in FIG. 12 to convert from magnitude to fault length, it may be possible to determine the statistical size distribution for this active fault population. FIG. 16 is a histogram of the earthquake data of FIG. 15, FIG. 16 showing the statistical distribution of hypocenter depth. Information about the ranges of earthquake depth is necessary to determine if there is a nearby source of water to infiltrate the fault zones and host the hydration reaction process. Earthquake depth may also be related to the geothermal gradient, which determines whether active faults exposed to an influx of water can carry out the hydration reaction within the optimal temperature ranges.

FIG. 17 illustrates a discrete fracture network representation of resolved active faults represented as equivalent area representations. In at least one embodiment, the exposed surface area for each discrete fault is proportionate to potential hydrogen reactivity. Output 1702 shows one possible realization of a fault plane with connected fractures generated from the active faults. FIG. 18 illustrates a discrete fracture network representation of resolved active faults represented as equivalent volume representations. In at least one embodiment, the exposed volume is proportionate to potential hydrogen reactivity. The volume may be determined by the area of each fault and any connected fractures that facilitate leak-off into or water influx from the host rock. FIG. 19 illustrates an example concept for natural hydrogen production in faulted basement source rock.

The methods described herein may be implemented on a computer system. In at least embodiment, the methods may be implemented on computer system 2002 of FIG. 20. As shown in FIG. 20, the exploration and production computer system 2002 includes an analysis tool 2004, a data repository 2006 for storing input data, intermediate data, and resultant outputs of the analysis tool 2004, and a user interface 2006. The computer system 2002 is connected to a network 2001 and may access earthquake data from the earthquake data repository 2008. The data repository 2006 may include a repository 2010 for subsurface fault parameters, a repository 2012 for active seismic zones, a repository 2014 for active fault volumes, a repository 2016 for water source fluxes, a repository 2018 for source rock exposure areas, a repository 2020 for framework models, and a repository 2022 for production predictions. The analysis tool 2004 may include a module 2024 for active seismic zone identification, a module 2026 for active fault volume building, a module 2028 for water source connection identification, a module 2030 for source rock exposure identification, a module 2032 for source rock exposure area calculation, and a module 2034 for production prediction calculation.

The computer system 2002 may be part of, integrated with, or independent from any of the features described with respect to FIG. 21, FIG. 22, and FIG. 23.

FIG. 21 is an example of a block diagram of a system 2100 for natural hydrogen exploration using fault data. The system 2100 can be implemented using one or more modules, shown in block form in the drawings. The one or more modules can be in software or hardware form, or a combination thereof. In some examples, the system 2100 can be implemented as machine readable instructions for execution on one or more computing platforms 2102 (referred to as a computing platform herein), as shown in FIG. 21. The computing platform 2102 can include one or more computing devices selected from, for example, a desktop computer, a server, a controller, a blade, a mobile phone, a tablet, a laptop, a personal digital assistant (PDA), and the like.

The computing platform 2104 can include a processor 2104 and a memory 2106. By way of example, the memory 2106 can be implemented, for example, as a non-transitory computer storage medium, such as volatile memory (e.g., random access memory), non-volatile memory (e.g., a hard disk drive, a solid-state drive, a flash memory, or the like), or a combination thereof. The processor 2104 can be implemented, for example, as one or more processor cores. The memory 2106 can store machine-readable instructions that can be retrieved and executed by the processor 2104 to implement the system 2100. Each of the processor 2104 and the memory 2106 can be implemented on a similar or a different computing platform. The computing platform 2102 can be implemented in a cloud computing environment (for example, as disclosed herein) and thus on a cloud infrastructure. In such a situation, features of the computing platform 2102 can be representative of a single instance of hardware or multiple instances of hardware executing across the multiple of instances (e.g., distributed) of hardware (e.g., computers, routers, memory, processors, or a combination thereof). Alternatively, the computing platform 2102 can be implemented on a single dedicated server or workstation.

In view of the structural and functional features described above, example methods will be better appreciated with reference to FIGS. 6 and 7. While, for purposes of simplicity of explanation, the example methods of FIGS. 6 and 7 are shown and described as executing serially, it is to be understood and appreciated that the present examples are not limited by the illustrated order, as some actions could in other examples occur in different orders, multiple times and/or concurrently from that shown and described herein. Moreover, it is not necessary that all described actions be performed to implement the methods, and conversely, some actions may be performed that are omitted from the description.

In view of the foregoing structural and functional description, those skilled in the art will appreciate that portions of the embodiments may be embodied as a method, data processing system, or computer program product. Accordingly, these portions of the present embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware, such as shown and described with respect to the computer system of FIG. 22. Furthermore, portions of the embodiments may be a computer program product on a computer-readable storage medium having computer readable program code on the medium. Any non-transitory, tangible storage media possessing structure may be utilized including, but not limited to, static and dynamic storage devices, volatile and non-volatile memories, hard disks, optical storage devices, and magnetic storage devices, but excludes any medium that is not eligible for patent protection under 35 U.S.C. § 111 (such as a propagating electrical or electromagnetic signals per se). As an example and not by way of limitation, computer-readable storage media may include a semiconductor-based circuit or device or other IC (such, as for example, a field-programmable gate array (FPGA) or an ASIC), a hard disk, an HDD, a hybrid hard drive (HHD), an optical disc, an optical disc drive (ODD), a magneto-optical disc, a magneto-optical drive, a floppy disk, a floppy disk drive (FDD), magnetic tape, a holographic storage medium, a solid-state drive (SSD), a RAM-drive, a SECURE DIGITAL card, a SECURE DIGITAL drive, or another suitable computer-readable storage medium or a combination of two or more of these, where appropriate. A computer-readable non-transitory storage medium may be volatile, nonvolatile, or a combination of volatile and non-volatile, as appropriate.

Certain embodiments have also been described herein with reference to block illustrations of methods, systems, and computer program products. It will be understood that blocks and/or combinations of blocks in the illustrations, as well as methods or steps or acts or processes described herein, can be implemented by a computer program comprising a routine of set instructions stored in a machine-readable storage medium as described herein. These instructions may be provided to one or more processors of a general purpose computer, special purpose computer, or other programmable data processing apparatus (or a combination of devices and circuits) to produce a machine, such that the instructions of the machine, when executed by the processor, implement the functions specified in the block or blocks, or in the acts, steps, methods and processes described herein.

These processor-executable instructions may also be stored in computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture including instructions which implement the function specified. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to realize a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in flowchart blocks that may be described herein.

In this regard, FIG. 22 illustrates one example of a computer system 2200 that can be employed to execute one or more embodiments of the present disclosure. Computer system 2200 can be implemented on one or more general purpose networked computer systems, embedded computer systems, routers, switches, server devices, client devices, various intermediate devices/nodes or standalone computer systems. Additionally, computer system 2200 can be implemented on various mobile clients such as, for example, a personal digital assistant (PDA), laptop computer, pager, and the like, provided it includes sufficient processing capabilities.

Computer system 2200 includes processing unit 2202, system memory 2204, and system bus 2206 that couples various system components, including the system memory 2204, to processing unit 2202. System memory 2204 can include volatile (e.g. RAM, DRAM, SDRAM, Double Data Rate (DDR) RAM, etc.) and non-volatile (e.g. Flash, NAND, etc.) memory. Dual microprocessors and other multi-processor architectures also can be used as processing unit 2202. System bus 2206 may be any of several types of bus structure including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. System memory 2204 includes read only memory (ROM) 2210 and random access memory (RAM) 2212. A basic input/output system (BIOS) 2214 can reside in ROM 2210 containing the basic routines that help to transfer information among elements within computer system 2200.

Computer system 2200 can include a hard disk drive 2216, magnetic disk drive 2218, e.g., to read from or write to removable disk 2220, and an optical disk drive 2222, e.g., for reading CD-ROM disk 2224 or to read from or write to other optical media. Hard disk drive 2216, magnetic disk drive 2218, and optical disk drive 2222 are connected to system bus 2206 by a hard disk drive interface 2226, a magnetic disk drive interface 2228, and an optical drive interface 2230, respectively. The drives and associated computer-readable media provide nonvolatile storage of data, data structures, and computer-executable instructions for computer system 2200. Although the description of computer-readable media above refers to a hard disk, a removable magnetic disk and a CD, other types of media that are readable by a computer, such as magnetic cassettes, flash memory cards, digital video disks and the like, in a variety of forms, may also be used in the operating environment; further, any such media may contain computer-executable instructions for implementing one or more parts of embodiments shown and described herein.

A number of program modules may be stored in drives and RAM 2210, including operating system 2232, one or more application programs 2234, other program modules 2236, and program data 2238. In some examples, the application programs 2234 can include a module 2224 for active seismic zone identification, a module 2026 for active fault volume building, a module 2028 for water source connection identification, a module 2030 for source rock exposure identification, a module 2032 for source rock exposure area calculation, and a module 2034 for production prediction calculation, and the program data 2238 can include a repository 2010 for subsurface fault parameters, a repository 2012 for active seismic zones, a repository 2014 for active fault volumes, a repository 2016 for water source fluxes, a repository 2018 for source rock exposure areas, a repository 2020 for framework models, and a repository 2022 for production predictions. The application programs 2234 and program data 2238 can include functions and methods programmed to enhance natural hydrogen exploration using fault data, such as shown and described herein.

A user may enter commands and information into computer system 2200 through one or more input devices 2240, such as a pointing device (e.g., a mouse, touch screen), keyboard, microphone, joystick, game pad, scanner, and the like. These and other input devices 2240 are often connected to processing unit 2202 through a corresponding port interface 2242 that is coupled to the system bus, but may be connected by other interfaces, such as a parallel port, serial port, or universal serial bus (USB). One or more output devices 2244 (e.g., display, a monitor, printer, projector, or other type of displaying device) is also connected to system bus 2206 via interface 2246, such as a video adapter.

Computer system 2200 may operate in a networked environment using logical connections to one or more remote computers, such as remote computer 2248. Remote computer 2248 may be a workstation, computer system, router, peer device, or other common network node, and typically includes many or all the elements described relative to computer system 2200. The logical connections, schematically indicated at 2250, can include a local area network (LAN) and/or a wide area network (WAN), or a combination of these, and can be in a cloud-type architecture, for example configured as private clouds, public clouds, hybrid clouds, and multi-clouds. When used in a LAN networking environment, computer system 2200 can be connected to the local network through a network interface or adapter 2252. When used in a WAN networking environment, computer system 2200 can include a modem, or can be connected to a communications server on the LAN. The modem, which may be internal or external, can be connected to system bus 2206 via an appropriate port interface. In a networked environment, application programs 2234 or program data 2238 depicted relative to computer system 2200, or portions thereof, may be stored in a remote memory storage device 2254.

Although this disclosure includes a detailed description on a computing platform and/or computer, implementation of the teachings recited herein are not limited to only such computing platforms. Rather, embodiments of the present disclosure are capable of being implemented in conjunction with any other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models (e.g., software as a service (Saas, platform as a service (PaaS), and/or infrastructure as a service (IaaS)) and at least four deployment models (e.g., private cloud, community cloud, public cloud, and/or hybrid cloud). A cloud computing environment can be service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability.

FIG. 23 is an example of a cloud computing environment 2300 that can be used for implementing one or more modules and/or systems in accordance with one or more examples, as disclosed herein. Thus, reference can be made to one or more examples of FIGS. 1-XX in the example of FIG. 23. As shown, cloud computing environment 2300 can include one or more cloud computing nodes 2302 with which local computing devices used by cloud consumers (or users), such as, for example, personal digital assistant (PDA), cellular, or portable device 2304, a desktop computer 2306, and/or a laptop computer 2308, may communicate. The computing nodes 2302 can communicate with one another. In some examples, the computing nodes 2302 can be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds, or a combination thereof. This allows the cloud computing environment 2300 to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. The devices 2304-2308, as shown in FIG. 23, are intended to be illustrative and that computing nodes 2302 and cloud computing environment 2300 can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser). In some examples, the one or more computing nodes 2302 are used for implementing one or more examples disclosed herein relating to root-source identification. Thus, in some examples, the one or more computing nodes can be used to implement modules, platforms, and/or systems, as disclosed herein.

In some examples, the cloud computing environment 2300 can provide one or more functional abstraction layers. It is to be understood that the cloud computing environment 2300 need not provide all of the one or more functional abstraction layers (and corresponding functions and/or components), as disclosed herein. For example, the cloud computing environment 2300 can provide a hardware and software layer that can include hardware and software components. Examples of hardware components include: mainframes; RISC (Reduced Instruction Set Computer) architecture based servers; servers; blade servers; storage devices; and networks and networking components. In some embodiments, software components include network application server software and database software.

In some examples, the cloud computing environment 2300 can provide a virtualization layer that provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers; virtual storage; virtual networks, including virtual private networks; virtual applications and operating systems; and virtual clients. In some examples, the cloud computing environment 2300 can provide a management layer that can provide the functions described below. For example, the management layer can provide resource provisioning that can provide dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. The management layer can also provide metering and pricing to provide cost tracking as resources are utilized within the cloud computing environment 2300, and billing or invoicing for consumption of these resources. In one example, these resources may include application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. The management layer can also provide a user portal that provides access to the cloud computing environment 2300 for consumers and system administrators. The management layer can also provide service level management, which can provide cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment can also be provided to provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA.

In some examples, the cloud computing environment 2300 can provide a workloads layer that provides examples of functionality for which the cloud computing environment 2300 may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation; software development and lifecycle management; virtual classroom education delivery; data analytics processing; and transaction processing. Various embodiments of the present disclosure can utilize the cloud computing environment 2300.

The present disclosure is also directed to the following exemplary embodiments, which can be practiced in any combination thereof:

A. A method for hydrogen exploration, the method including obtaining one or more hydrogen prospects, the one or more hydrogen prospects selected based on one or more parameters. The method further including constructing one or more fracture networks based on the one or more hydrogen prospects, the one or more fracture networks each having a source rock area value. The method further including, based on the source rock area value for each of the one or more hydrogen prospects, generating a source rock exposure value for each of the one or more prospects. The method further including outputting a production prediction based on the source rock exposure value for each of the one or more hydrogen prospects.

B. A system for hydrogen exploration including a memory and one or more processors. The one or more processors are configured to cause the apparatus to obtain one or more hydrogen prospects, the one or more hydrogen prospects selected based on one or more parameters. The one or more processors are further configured to construct one or more fracture networks based on the one or more hydrogen prospects, the one or more fracture networks each having a source rock area value. The one or more processors are further configured to, based on the source rock area value for each of the one or more hydrogen prospects, generate a source rock exposure value for each of the one or more prospects. The one or more processors are further configured to output a production prediction based on the source rock exposure value for each of the one or more hydrogen prospects.

Each of embodiments A through B may have one or more of the following additional elements in any combination: Element 1: The one or more hydrogen prospects are selected based on at least one of rock characteristics of the one or more hydrogen prospects, fault characteristics of the one or more hydrogen prospects, and earthquake catalog data of the one or more hydrogen prospects. Element 2: Constructing the one or more fracture networks based on the one or more hydrogen prospects includes defining a set of subsurface fault parameters for each of the one or more hydrogen prospects, the set subsurface fault parameters characterizing an active seismic zone. Constructing the one or more fracture networks based on the one or more hydrogen prospects further includes delineating, based on a comparison of the set of subsurface fault parameters and the active seismic zone, an active fault volume. Element 3: Constructing the one or more fracture networks based on the one or more hydrogen prospects further includes identifying a set of connections between the active fault volume and at least one water source. Constructing the one or more fracture networks based on the one or more hydrogen prospects further includes identifying, based on the set of connection, water source flux. Element 4: Constructing the one or more fracture networks based on the one or more hydrogen prospects further includes forming a source rock exposure surface. Constructing the one or more fracture networks based on the one or more hydrogen prospects further includes generating an area of the source rock exposure surface based on a framework model of the active fault volume.

Element 5: Outputting a production prediction based on the source rock exposure value for each of the one or more hydrogen prospects includes calculating the production prediction based on at least one of the area of the source rock exposure surface and the water source flux. Element 6: Forming the source rock exposure surface includes comparing the active fault volume to a source rock volume. Forming the source rock exposure surface includes identifying exposure points on the active fault volume to generate the source rock exposure surface. Element 7: The framework model is generated using at least a statistical distribution of earthquakes. Element 8: The framework model is generated using a discrete fracture network (DFN) model. Element 9: The DEN model is constructed based on geological data. Element 10: The framework model is generated using equivalent volume data. Element 11: Extracting, based on the production prediction, natural hydrogen from a fractured subsurface reservoir represented by at least one of the one or more hydrogen prospects. Element 12: The one or more hydrogen prospects represent fractured subsurface reservoirs connected to active fault systems. Element 13: The production prediction estimates a natural hydrogen gas volume accumulated in the one or more hydrogen prospects

By way of non-limiting example, exemplary combinations applicable to A through B include: Element 1 with any one of Elements 2-12; Element 2 with any one of Elements 1 and 3-12; Element 3 with any one of Elements 1-2 and 4-12; Element 4 with any one of Elements 1-3 and 5-12; Element 5 with any one of Elements 1-4 and 6-12; Element 6 with any one of Elements 1-5 and 6-12; Element 7 with any one of Elements 1-6 and 8-12; Element 8 with any one of Elements 1-7 and 9-12; Element 9 with any one of Elements 1-8 and 10-12; Element 10 with any one of Elements 1-9 and 11-12; Element 11 with any one of Elements 1-10 and 12; and Element 12 with any one of Elements 1-11.

The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention. The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.

Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, for example, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “contains”, “containing”, “includes”, “including,” “comprises”, and/or “comprising,” and variations thereof, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

Terms of orientation used herein are merely for purposes of convention and referencing and are not to be construed as limiting. However, it is recognized these terms could be used with reference to an operator or user. Accordingly, no limitations are implied or to be inferred. In addition, the use of ordinal numbers (e.g., first, second, third, etc.) is for distinction and not counting. For example, the use of “third” does not imply there must be a corresponding “first” or “second.” Also, if used herein, the terms “coupled” or “coupled to” or “connected” or “connected to” or “attached” or “attached to” may indicate establishing either a direct or indirect connection, and is not limited to either unless expressly referenced as such. Furthermore, to the extent that the terms “includes,” “has,” “possesses,” and the like are used in the detailed description, claims, appendices and drawings such terms are intended to be inclusive in a manner similar to the term “comprising” as “comprising” is interpreted when employed as a transitional word in a claim. The term “based on” means “based at least in part on.” The terms “about” and “approximately” can be used to include any numerical value that can vary without changing the basic function of that value. When used with a range, “about” and “approximately” also disclose the range defined by the absolute values of the two endpoints, e.g. “about 2 to about 4” also discloses the range “from 2 to 4.” Generally, the terms “about” and “approximately” may refer to plus or minus 5-10% of the indicated number.

While the disclosure has described several exemplary embodiments, it will be understood by those skilled in the art that various changes can be made, and equivalents can be substituted for elements thereof, without departing from the spirit and scope of the invention. In addition, many modifications will be appreciated by those skilled in the art to adapt a particular instrument, situation, or material to embodiments of the disclosure without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, or to the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the appended claims. Moreover, reference in the appended claims to an apparatus or system or a component of an apparatus or system being adapted to, arranged to, capable of, configured to, enabled to, operable to, or operative to perform a particular function encompasses that apparatus, system, or component, whether or not it or that particular function is activated, turned on, or unlocked, as long as that apparatus, system, or component is so adapted, arranged, capable, configured, enabled, operable, or operative.