OFFSET WELL ANALYSIS FOR DERIVING NEXT WELL DRILLING PARAMETERS

Description

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application Ser. No. 63/741,315, entitled “OFFSET WELL ANALYSIS FOR DERIVING NEXT WELL DRILLING PARAMETERS”, filed by Ketan Bhaidasna et al., on Jan. 2, 2025, which is commonly assigned with this application and incorporated herein by reference in its entirety.

TECHNICAL FIELD

This disclosure relates, generally, to drilling wells, and more specifically, to drilling wells using drilling parameters based on the analysis of previous well data.

BACKGROUND

Accessing hydrocarbon reserves, such as gas or oil reserves, typically involves creating a well by drilling into the earth using a drill bit. The drill bit is part of a bottom hole assembly (BHA) located at the downhole end of a drill string, which includes multiple drill pipes connected together. In addition to the drill bit, the BHA includes other components, such as stabilizers, drill collars, measuring equipment or sensors, and directional drilling equipment. A top drive is used at the surface of the well to turn the drill string, which rotates the drill bit and extends the well into the earth. For drilling a new well, the lessons learned from prior nearby wells can be assessed to assist in determining, for example, what drilling parameters to use.

SUMMARY

In one aspect, the disclosure provides a method of drilling a well. In one example, the method includes: (1) deriving statistical information from data of previous wells that includes confidence intervals and one or more limiter overlays, wherein the previous well data includes rate of penetration (ROP) maps from bit rock models of the previous wells, (2) ascertaining drilling parameters for a current well using a bit rock model of the current well, (3) drilling the current well using the drilling parameters, (4) detecting a drilling challenge during the drilling of the current well, wherein drilling challenges occur when one of the drilling parameters is outside of a corresponding one of the confidence intervals, (5) applying, when determining one of the one or more limiter overlays corresponds to the drilling challenge, the corresponding one of the one or more limiter overlays, (6) identifying an action for the drilling of the current well according to the corresponding one of the one or more limiter overlays, and (7) continuing the drilling of the current well according to the action.

In another aspect a drilling computing system is disclosed. In one example, the drilling computing system includes: (1) one or more memories having operating instructions for drilling a current well using statistical information from previous well data and drilling parameters ascertained from a bit rock model of the current well, wherein the statistical information includes one or more of limiter overlays and confidence intervals, and (2) one or more processors configured to perform operations according to the operating instructions, wherein the operations include (2A) detecting a drilling challenge during the drilling of the current well, wherein drilling challenges occur when one of the drilling parameters is outside of a corresponding one of the confidence intervals, (2B) applying, when determining one of the one or more limiter overlays corresponds to the drilling challenge, the corresponding one of the one or more limiter overlays, (2C) identifying an action for the drilling of the current well according to the corresponding one of the one or more limiter overlays, and (2D) continuing the drilling of the current well according to the action.

In yet another aspect, a well system for drilling a current well is disclosed. In one example the well system includes: (1) surface equipment and (2) one or more processors configured to

perform operations including (2A) ascertaining drilling parameters for the current well using a bit rock model generated using surface data from the surface equipment, (2B) detecting a drilling challenge during drilling of the current well using the drilling parameters, wherein a drilling challenge occurs when one of the drilling parameters is outside of a confidence interval derived from previous well data, (2C) adjusting one or more of the drilling parameters according to at least one limiter overlay when the at least one limiter overlay corresponds to the drilling challenge, wherein the at least one limiter overlay is derived from the previous well data, and (2D) maintaining the drilling parameters when determining the limiter overlay does not correspond to the drilling challenge.

BRIEF DESCRIPTION

Reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:

FIG. 1 illustrates an example of a drilling system configured to perform formation drilling to create a wellbore or well according to the principles of the disclosure;

FIG. 2 illustrates a block diagram of an example of a drilling system constructed according to the principles of the disclosure;

FIG. 3 illustrates a flow diagram of an example of method of generating statistical information from previous well data for a current well according to the principles of the disclosure;

FIG. 4 illustrates a flow diagram of an example method of generating a confidence interval for a drilling parameter according to the principles of the disclosure;

FIG. 5 illustrates diagrams of examples of using statistical information with real time current well data for drilling the current well according to the principles of the disclosure;

FIG. 6 illustrates a flow diagram of an example of a method of drilling a well according to the principles of the disclosure;

FIG. 7 illustrates a flow diagram of another example method of drilling a well according to the principles of the disclosure; and

FIG. 8 illustrates a block diagram of an example of a computing system configured to perform the various methods disclosed herein

DETAILED DESCRIPTION

Determining drilling parameters from previously drilled wells, such as offset wells, is typically made on an ad-hoc basis that focuses on the severe difficulties that were encountered during the drilling. As such, the present analysis of previous well data fails to provide a finely discretized roadmap of drilling parameters to use and an expected performance, such as rate of penetration (ROP) for any given depth. In addition, the present analysis does not consider the effects of formation on the drilling and does not characterize dysfunction on drilling parameters to assess in real-time for expected results versus achieved results.

The disclosure, therefore, provides a system and method for using previous well data and well data from a current well (i.e. current well data) to improve the drilling of the current well. The previous well data is analyzed and statistical information is derived from the analysis, which is used for drilling the current well. Analysis of the previous well data derives idealized parameters to predict performance and adds capability to combine various overlays of drilling conditions to give a comprehensive road map for drilling a next well in real time. Real-time data generated during drilling of the current well is compared to the statistical information to identify any drilling challenges that may need to be addressed. The combination of the previous well data and the current well data can also be used to provide guidance for the drilling of additional future wells.

The previous well data is from already drilled wells of interest that have similar geology or tools as the current well being drilled. The previous well data can be from different wells depending on the type of analysis and the resultant statistical information. For geological analysis, for example, data from a well having a similar formation as the current well is desired. As such, the previous well data can be from offset wells that are proximate to the current well and have a similar geology. For analyzing bit performance, the previous well data can be from wells that used the same drill bit as the one being used in the current well. Accordingly, the previous well data can also be from other wells that may not be proximate to the current well but used one or more tools being used in the current well. Thus, the previous well data can be from multiple sources that correspond to the type of analysis being performed to generate the statistical information.

The statistical information generated from the previous well data is beneficiary for drilling the current well. For example, the statistical information can include one or more of bit rock data, optimized recommendations for drilling parameters, confidence intervals for drilling parameters, and limiter overlays. Limiter overlays are developed from the previous well data and used to improve performance when drilling the current well. During drilling of previous wells, some drilling parameters may be reduced or increased due to the formation, a dysfunction or adverse condition, or a steering requirement (i.e., collectively referred to as limiters). An overlay can be generated for one or more, such as for each, of the limiters and applied to improve drilling of the current well.

The limiter overlays identify particular features encountered during drilling of the previous wells and include corresponding drilling parameters associated with the features that can be used to adjust the drilling parameters of the current well when similar features are encountered. Formation overlays, steering overlays, and challenge overlays are examples of overlays discussed herein. The challenge overlays correspond to adverse conditions encountered during drilling of the previous wells and provide drilling parameters associated with the different adverse conditions that can be used to adjust the current drilling operation for improved performance. Examples of adverse conditions include bit wear, stick slip, whirl, telemetry, Geo-Steering, high frequency torsional oscillations (HFTOs), hole cleaning, washout, pack-off, managed temperature drilling, stringer, and steering limitations.

Different types of previous well data from the different wells of interest can be used for the different types of statistical information. For example, the statistical information can be a bit rock interface or model and the type of previous well data used to derive the bit rock model can be surface data from a well system, such as well system 100 of FIG. 1. The surface data includes, for example, one or more of block position, bit depth, flow-in of drilling fluid, hole depth (or measured depth), hookload, rate of penetration (ROP), revolutions per minute (RPM), stand-pipe pressure (SPP), timestamp, surface torque, and weight on bit (WOB).

FIG. 1 illustrates an example of a well system 100 configured to perform formation drilling to create a wellbore or well 101. The well system 100 can be, for example, a logging-while-drilling (LWD) system or a measurement-while-drilling (MWD) system. FIG. 1 depicts an onshore operation. Those skilled in the art will understand that the disclosure is equally well suited for use in offshore operations or onshore operations over a body of water. The well system 100 includes a BHA 120 that includes a drill bit 110 that is operatively coupled to a tool string 150, which may be moved axially within the wellbore 101. During operation, the drill bit 110 penetrates the earth 102 and thereby creates the wellbore 101. BHA 120 provides directional control of the drill bit 110 as it advances into the earth 102. Tool string 150 can be semi-permanently mounted with various measurement tools (not shown) such as, but not limited to, MWD and LWD tools, that may be configured to take downhole measurements of drilling conditions and geological formation of the earth 102. The measurement tools can include sensors, such as magnetometers, accelerometers, gyroscope, etc.

The well system 100 is configured to drive the BHA 120 positioned or otherwise arranged at the bottom of the drill string 125 extended into the earth 102 from a derrick 130 arranged at the surface 104. The well system 100 includes a top drive 131 that is used to rotate the drill string 125 at the surface 104, which then rotates the drill bit 110 in the wellbore 101. Operation of the top drive 131 is controlled by a top drive controller. RPMs of the top drive 131 can be set and adjusted per statistical information from previous well data. The well system 100 can also include a kelly and a traveling block that is used to lower and raise the kelly and drill string 125, which can be used to adjust the WOB.

Fluid or “drilling mud” from a mud tank 140 may be pumped downhole using a mud pump 142 powered by an adjacent power source, such as a prime mover or motor 144. The rate of the mud flow may be set and controlled according to the statistical information using the mud pump 142. The drilling mud may be pumped from mud tank 140, through a standpipe 146, which feeds the drilling mud into drill string 125 and conveys the same to the drill bit 110. The drilling mud exits one or more nozzles arranged in the drill bit 110 and in the process cools the drill bit 110. After exiting the drill bit 110, the mud circulates back to the surface 104 via the annulus defined between the wellbore 101 and the drill string 125, and in the process, returns drill cuttings and debris to the surface. The cuttings and mud mixture are passed through a flow line 148 and are processed such that a cleaned mud is returned down hole through the standpipe 146 once again.

The well system 100 also includes a well site controller 160 (a computing device), and a computing system 164, which can be communicatively coupled to well site controller 160. Well site controller 160 is configured to direct operation of the well system 100 and includes one or more processors (or processing units) and one or more memories.

Well site controller 160 or computing system 164, can be utilized to communicate with downhole tools of the tool string 150, such as sending and receiving telemetry data, drilling sensor data, instructions, and other information, including but not limited to collected or measured parameters, location within the wellbore 101, and cuttings information. A communication channel may be established by using, for example, electrical signals or mud pulse telemetry for most of the length of the tool string 150 from the drill bit 110 to the controller 160.

The controller 160, or a separate computing device such as computing system 164 or another processing unit or processor can be configured to perform one or more of the functions as disclosed herein. For example, the controller 160, the computing system 164, or a combination thereof can be configured to determine new drilling parameters or actions to take by analyzing both real-time current well data and previous well data. Computing system 164 can be proximate well site controller 160 or be distant, such as in a cloud environment, a data center, a lab, or a corporate office. Computing system 164 can be a laptop, smartphone, personal digital assistant (PDA), server, desktop computer, cloud computing system, other computing systems, or a combination thereof, that are operable to perform the processes and methods described herein. Well site operators, engineers, and other personnel can send and receive data, instructions, measurements, and other information by various conventional means with computing system 164 or well site controller 160. The well site controller 160 and/or the computing system 164 can include a screen that displays the comparison of the real-time current well data with the statistical information derived from the previous well data. FIG. 5 provides an example of the real time assessment of current well data compared to confidence intervals that can be displayed on the screen and screen 234 provides an example of a screen. A human operator can then initiate an action based on, for example, reviewing the screen. Instead of a visual representation, a human operator can also take or initiate an action based on audio/digital messaging. Actions include, for example, changing a drilling parameter, such as WOB, RPMs, rate of flow, etc., replacing the drill bit 110, and cleaning the wellbore 101. Taking an action can also be automatically initiated by a computing system analyzing the data, such as the data shown in FIG. 5. The computing system can be the well site controller 160 or the computing system 164.

FIG. 2 illustrates a block diagram of an example of a drilling system 200 constructed according to the principles of the disclosure. Drilling system 200 is configured to direct a drilling operation at a well, such as well system 100, based on current well data and statistical information from previous well data. Drilling system 200 includes a drilling analyzer 210 and a controller 230. Controller 230 is an example of well site controller 160. The drilling analyzer 210 and the controller 230 can be implemented on a computing system that includes the necessary logic to perform the functions disclosed herein. FIG. 8 provides an example of such a computing system. The drilling analyzer 210 and controller 230 can be integrated into a single computing device.

Drilling analyzer 210 is configured to perform an analysis on previous well data and generate statistical information therefrom. The previous well data can be from different wells of interest that are associated with the current well, such as through geology or tools. The previous well data can be stored in a data reservoir of well data from already drilled wells. The previous well data can be, for example, surface data. The data reservoir can include public data, proprietary data, or a combination thereof. Drilling analyzer 210 is configured to derive each of the different types of statistical information from the previous well data. For example, drilling analyzer 210 can derive statistical information according to method 300 of FIG. 3 and/or method 700 of FIG. 7. The generated statistical information can be saved and provided to controller 230.

Controller 230 is configured to control the drilling operation of the current well. In addition to the statistical information, controller 230 also receives well data from the current well being drilled and uses both to direct drilling of the current well. The current well data is real-time data that is received via sensors and/or equipment of the current well, such as sensors and equipment of well system 100.

Controller 230 is configured to compare the current well data to at least some of the statistical information to direct drilling of the current well. For example, controller 230 can compare current well data to confidence intervals derived from the previous well data to identify any drilling challenges with the current well. The current well data used for the comparison includes data that corresponds to the type of previous well data used to derive each particular type of statistical information. For example, data used to generate confidence intervals and median values for the previous well data for a particular parameter, such a DOC, would be the same type of real-time data used from drilling of the current well for comparison. Controller 230 can initiate an action based on a comparison of the statistical information and current well data. The action can be based on a limiter overlay, such as a challenge overlay that corresponds to the drilling challenge.

Controller 230 can provide the current well data with respect to at least some of the statistical information to screen 234. FIG. 5 illustrates an example of current well data presented with respect to the median values and confidence intervals per each depth for different drilling parameters that can be displayed on screen 234. An operator of the well can monitor screen 234 and manually initiate an action based on the presented visual data. The controller 230 can generate a signal to initiate the action. The action can be based on a limiter overlay that corresponds to a drilling challenge identified from the review of the data. For example, an operator can initiate an action that adjusts a drilling parameter when a drilling challenge is identified, such as when a drilling parameter is outside of a confidence interval. Controller 230 can be configured to automatically perform the identifying and/or initiating the action. Other examples of actions besides adjusting one or more drilling parameters, such as WOB or RPM, include generating an alarm, cleaning the hole of the current well, or replacing the drill bit being used for the drilling.

FIG. 3 illustrates a flow diagram of an example of method 300 of generating statistical information from previous well data for a current well according to the principles of the disclosure. A drilling analyzer as disclosed herein can be configured to perform the steps of method 300. Method 300 begins in step 305.

In step 310, previous wells of interest that correspond to the current well are selected. The previous wells can correspond to the current well based on similarities of geology and/or similar well tools. The previous wells and data therefrom can be saved in a data reservoir. The previous wells of interest can be manually selected or automatically selected via a search algorithm.

Drilling parameters and rock bit data from the previous wells are ascertained in step 320. From the selected wells, the previous well data is analyzed to determine a bit rock model and drilling parameters from the previous wells. The bit rock model can be a physics based model of bit/rock interaction which is derived from tagging bottom and fitting drilling parameters. The model provides a space in which drilling parameters can be selected for the highest ROP. Previous wells can be drilled using the drilling parameters to provide an effective drilling parameter used and ROP achieved that can then be used for drilling the current well.

-Thus, the bit rock model can be used to determine drilling efficiency and can be defined on different drilling characteristics (such as depth of cut (DOC), weight-on-bit (WOB), and torque-on-bit (TOB)). The data driven physical model can be generated via an algorithm (or algorithms) using surface data and provide optimized recommendations for parameters like WOB, Flow and RPM. For example, the bit rock model can by modeled by a relationship between WOB and DOC, which can be equated to ROP divided by RPM.

In step 330, the drilling parameters are used to build depth versus drilling parameters and results using the drillings parameters and ROP from the well bit rock data. The drilling parameters, for example, are directed to obtaining an optimized ROP for the current well at each depth of the well. In other words, the drilling parameters that resulted in the best ROP along the different depths of the previous wells can be used as optimized drilling parameters for the current well.

Confidence intervals for drilling parameters are determined from the previous well data in step 340. The confidence intervals can be determined according to method 400 of FIG. 4. The confidence intervals can differ for each depth of a well for a particular drilling parameter and can differ at each depth for the different drilling parameters. FIG. 5 illustrates an example of the confidence intervals for various drilling parameters. Other statistical methods can also be employed to calculate confidence intervals. A machine learning model can also be used to determine the confidence intervals. For example, a dataset of drilling data can be used to teach a model an operating range for different parameters by recognizing patterns of parameter values for different drilling conditions. An algorithm can direct this iterative process of hyperparameter tuning and model evaluation. The trained model can then be used to generate the confidence intervals from the previous well data.

In step 350, limiter overlays are generated from the previous well data. When drilling the previous wells, various actions could have been taken in response to certain limiting conditions due to, for example, the formation, steering requirements, and/or adverse drilling conditions. The limiter overlays identify those actions that can be used to make adjustments when a similar limiting condition, referred to herein as a drilling challenge, occurs during drilling of the current well. A drilling challenge is the occurrence of a drilling parameter that is outside of a confidence interval for a defined amount of depth. The amount of depth can be in feet (or meters), a stand, or multiple stands. As disclosed previously, actions include, for example, changing drilling parameters, replacing a bit, cleaning the hole, etc.

Various methods, including statistical, rules based, or machine learning can be used to generate the limiter overlays. For example, a dataset of drilling data can be used to teach a model to recognize patterns of different limiting conditions and actions corresponding to the limiting conditions that were taken. An algorithm can direct the iterative process of hyperparameter tuning and model evaluation to provide a trained model that can then be used to generate the limiter overlays from the previous well data.

The statistical information is saved in step 360. The statistical information can be saved, for example, in the memory of a controller, such as well site controller 160 or controller 230, a drilling analyzer, such as drilling analyzer 210, or another memory or data storage. An example of the statistical information that can be generated and saved includes optimized drilling parameters, confidence intervals, limiter overlays, and bit rock data. Method 300 continues to step 370 and ends. Method 300 can be repeated for other future wells using previous well data that is of interest for each of other future wells.

FIG. 4 illustrates a flow diagram of an example method 400 of generating a confidence interval for a drilling parameter according to the principles of the disclosure. Method 400 can be used for various types of drilling parameters, such as DOC, WOB, bit wear indicator, and rock strength, which are all represented in FIG. 5. Method 400 can be executed by a drilling analyzer, such as drilling analyzer 210. Method 400 begins in step 405.

In step 410, a median value of the drilling parameter is determined from the previous well data. The previous well data is from multiple wells and is provided at each depth, such as at each foot, stand, or multiple stands. The median value is then determined per each depth from the multiple values of the previous well data at each depth. The median values can be determined according to typical methods of determining a median value from multiple values.

In step 420, a graph of the median values is smoothed. Various known techniques can be used to smooth the median values along the depths of the well to remove fluctuations.

A rolling standard deviation σ is determined in step 430 to define variability of the drilling parameter. The rolling standard deviation σ represents a standard deviation of the median values over a window that rolls through the median values at the different depths. The rolling standard deviation σ represents a volatility measurement of the dispersion of the median values within the window while moving over the depths.

In step 440, a confidence interval for the drilling parameter is determined using the median value and the standard deviation σ. For example, the confidence interval for the drilling parameter can be calculated using Equation 1.

Confidence ⁢ Interval = Median +/- 2 ⁢ σ Equation ⁢ 1

Method 400 ends in step 450. The generated confidence interval and the median values for the drilling parameter can be provided to a screen with the current well data for monitoring by an operator. An assessment of the current well data with respect to the confidence intervals can also be performed automatically by a computing device, such as controller 230. FIG. 5 provides an example of various drilling parameters and corresponding confidence intervals and current well data that can be viewed by an operator. For automatic implementations, data corresponding to the visual data can be analyzed by a computing system to provide an assessment and can also be used to initiate an action.

FIG. 5 illustrates diagrams of examples of using statistical information with real time current well data for drilling the current well according to the principles of the disclosure. As noted above, FIG. 5 illustrates a method for real-time performance assessment and expected next well prediction. Four different drilling parameters are shown for performance assessment using the statistical information of confidence intervals and median values. The four drilling parameters are DOC, WOB, bit wear indicator, and rock strength. Each of these drilling parameters are on the y axis of each graph wherein the x axis is the depth, which is in the unit of feet for FIG. 5. For FIG. 5, the previous well data is from offset wells as indicated.

Using the previous well data, a moving median and confidence intervals are derived, such as in method 400. In FIG. 5, the median values are the solid lines and are determined by obtaining the median value from the various offset well per each depth. The confidence intervals (CI in FIG. 5) are shown by the gray band. The confidence interval is the band in which the values for the current well are expected to fall. The dots of FIG. 5 represent the values for the current well being drilled. During drilling of the current well, one or more of the graphs of FIG. 5 can be displayed on a screen, such as screen 234, for review by an operator. There are two possibilities to consider for each of the drilling parameters. The first possibility is that the current well values fall within the respective confidence interval indicating that the current performance is as expected according to the previous well data. In this case no action is needed, such as changing the current drilling parameters. Shaded areas 510, 520, 530, and 540 illustrate where the current well values for the DOC, WOB, bit wear indicator, and rock strength fall within the respective confidence intervals.

The second possibility is if the current well values fall outside of the respective confidence intervals. Shaded areas 550, 560, 570, and 580 illustrate where at least some of the current well values for the DOC, WOB, bit wear indicator, and rock strength fall outside of the respective confidence intervals. In this case the reason why the current well values are outside of a confidence interval is analyzed to determine, such as based on a limiter overlay, what action is needed to align within the confidence intervals.

An operator can analyze the graphs of FIG. 5 to determine a reason why a real-time drilling parameter is not within a confidence interval. Consider, for example, DOC. As shown in area 550 the depth of cut is generally lower than the confidence interval between the depths of 5,000 to 6,000 feet. As shown in area 580, the rock strength is also generally higher than the confidence interval at the depths 5,000 to 6,000. By analyzing areas 550 and 580, the operator can deduce that the rock strength is higher than the expected value and determine if adjustments are needed to compensate for the higher rock strength. For example, the WOB can be increased or the RPM can be increased. The operator can also turn to a limiter overlay to determine an action to take due to a drilling challenge at a particular depth. A computing device can also automatically determine a drilling challenge, determine if one or more limiter overlay corresponds to the drilling challenge, apply the appropriate limiter overlay that corresponds, and adjust a drilling parameter according to the corresponding limiter overlay at the particular depth. Applying a limiter overlay changes the confidence interval and median value per depth of the respective parameters for future drilling at the current well. As such, the visual display would be changed and could be used for manual review by an operator.

FIG. 6 illustrates a flow diagram of an example of a method 600 of drilling a well according to the principles of the disclosure. Method 600 includes using statistical information from previous well data for drilling a current well. One or more of the steps of method 600 can be performed by one or more processors that are configured to operate according to a series of operating instructions that correspond to one or more algorithms directed to drilling a current well using statistical information from previous wells. In method 600, the statistical information are confidence intervals and limiter overlays. Steps of method 600 can be performed, for example, by a drilling analyzer, a well controller, or a combination thereof. One or more of the steps of method 600 can be performed automatically. Some of the steps of method 600 can also be performed manually, such as by an operator. Method 600 begins in step 605.

In step 610, statistical information from previous wells is derived. The statistical information can be derived according to method 300 of FIG. 3. The statistical information can include, for example, confidence intervals and limiter overlays.

Drilling parameters for the current well are obtained in step 620. The drilling parameters can be ascertained per a bit rock model of the current well. The bit rock model can be obtained using surface data from the current well. Downhole data, such as resistivity measurements, can be used to augment the surface data. The drilling parameters for the current well can be determined using the same calculations as the drilling parameters were determined using the previous well data.

In step 630, a visualization of the current well data with respect to the statistical information is provided. The statistical information can include the median operating values at each depth and the corresponding confidence intervals. FIG. 5 illustrates an example for multiple drilling parameters that can be displayed. The visualization can be provided to a screen, such as screen 234 of FIG. 2.

A drilling challenge of the current well is detected in step 640. A drilling challenge can occur, for example, when one of the drilling parameters is outside of a corresponding one of the confidence intervals. The drilling challenge can be detected manually by, for example, reviewing the visualization provide by step 630. The drilling challenge can also be detected automatically by assessing the current well data with respect to the previous well data. For automatic detection, an algorithm can be used to detect the occurrence of drilling challenges during real-time drilling.

In step 650, one or more drilling parameters is changed due to the detected drilling challenge. The one or more drilling parameters can be changed manually or automatically. The change can be identified by an action associated with a limiter overlay that corresponds to the drilling challenge, wherein the drilling challenge corresponds a limiting condition encountered during drilling of the previous wells. The limiter overlays indicate an action or actions performed during drilling of the previous wells to address and/or overcome the limiting condition that was encountered. For example, the action can be to increase the RPM of a drill bit by increasing the RPM of the top drive.

Method 600 proceeds to step 660 wherein drilling of the current well continues according to the action or actions that were identified. For example, drilling can continue using an adjusted one or more drilling parameters. When a limiter overlay does not correspond to the drilling challenge, drilling of the current well can continue using the ascertained drilling parameters for the current well. Method 600 ends at step 670.

FIG. 7 illustrates a flow diagram of another example method 700 of drilling a well according to the principles of the disclosure. Method 700 includes deriving statistical information from previous well data for drilling the current well. Offset well data will be used as an example of the previous well data for method 700. Steps of method 700 can be performed by one or more of a drilling analyzer or a controller, such as drilling analyzer 210 and controller 230. An operator can also manually perform one or more of the steps of method 700. Method 700 begins in step 705.

In step 710, statistical information is derived from offset well data. To derive the statistical information, the offset well data is first generated by drilling offset wells. Drilling parameters for drilling the offset wells are determined from a bit rock model derived from the offset well data. The bit rock model can be derived, for example, using surface data from the offset well data. For example, the bit rock model can be derived for each stand or for multiple stands, such as two stands. In addition to the surface data, downhole data may also be used to augment the surface data when deriving the bit rock interface. The derived bit rock model can be in a torque-WOB-DOC domain. The drilling parameters include WOB and RPM, and correspond to bit rock interfaces for each designated depth. For example, the WOB and the RPM can change per each stand or unit of depth based on the corresponding bit rock model. The statistical information from the offset well data includes confidence intervals, limiter overlays, or a combination thereof.

Drilling parameters for drilling the current well are determined in step 720 using a bit rock model for the current well. The drilling parameters can be determined as in step 620 of method 600. As such, the drilling parameters for the current well can be similarly determined according to the same procedure used to determine the drilling parameters for the offset wells.

The current well is drilled in step 730 using the drilling parameters and a real-time assessment of the current well data is made in step 740 in view of the statistical information from the offset well data. For example, occurrences of the current well data being outside of the confidence intervals can be identified, manually or automatically. Through monitoring of the current well data in view of the statistical information generated from the offset well data, correspondence of one or more different limiter overlays can be determined and then turned on or off as needed as drilling of the current well progresses at the different depths. As such, drilling parameters for drilling the current well can be further optimized through the assessment of the expected discovery of formation/dysfunction/steering predicted and change the operating envelope and resulting ROP from application of a limiter overlay. In some instances, even with the occurrence of a drilling challenge, a limiter overlay may not apply and the drilling parameters for the current well are not changed. For example, a detected drilling challenge may not correspond to a limiting condition of previous wells. As such, no predetermined actions for the particular drilling challenge are provided by a limiter overlay and the drilling continues using the existing drilling parameters determined from the current well bit rock interaction.

Different limiter overlays may correspond to a detected drilling challenge at different depths and a combination of the different overlays can then be applied for the different depths. Steps 750 to 770 disclose the different limiter overlays from the offset wells that can be applied, for example, turned on or off, to adjust the drilling parameters of the current well. In step 750, a formation overlay is applied. The formation overlay can be derived from the analysis of multiple types of formation information. For example, the offset well data can be from one or more of resistivity, porosity, acoustic, or magnetic measurements. A different layer of each type of formation data can used and applied to adjust the drilling parameters.

In step 760, limiter overlays of adverse conditions from the offset wells are applied to the drilling parameters. The limiter overlays were discovered from the offset well analysis and include drilling parameters that were changed due to an adverse condition that was encountered. Examples of adverse conditions include bit wear, HFTOs, stringer, and steering limitations. Other examples are denoted above.

In step 770, steering requirement overlays derived from the offset well data are also applied to the drilling parameters of the current well. The steering requirement overlays include changes to drilling parameters that were made due to particular steering requirements encountered during drilling of the offset wells.

In step 780, an action can be taken in view of the assessment and one or more of the limiter overlays. The action can, for example, change one or more drilling parameter, generate an alarm, change drilling equipment, or include a combination of multiple actions. The action or actions can be identified from the one or more corresponding limiter overlays. A signal, such as an electrical signal, can be generated and delivered to one or more piece of well equipment to initiate an action. Method 700 continues to step 790 and ends. As noted above, if a limiter overlay does not correspond to a detected drilling challenge, method 700 continues using the ascertained drilling parameters.

FIG. 8 illustrates a block diagram of an example of a computing system 800 configured to perform the various methods disclosed herein. Computing system 800 includes one or more interfaces represented by interface 810, one or more memories represented by memory 820, and one or more processors represented by processor 830. Computing system 800 can be a single integrated computing device or distributed over multiple computing devices. Computing system 800 can be at a well site and can be used to execute real-time changes in a drilling operation. In some examples, computing system 800 or at least a portion thereof can be implemented on a server. Computing system 800 can be configured to perform the functions of a drilling analyzer, such as drilling analyzer 210, a controller, such as controller 230, or both.

The interface 810 is a component or device interface configured to communicate (transmit and receive) data. The interface 810 can be a conventional interface that receives inputs and transmits outputs according to standard protocols. For example, the interface 810 can be configured to receive previous well data and output statistical information generated by the processor 830. The interface 810 can also receive additional input data such as previous well data and current well data, and can output an action, such as a change in drilling parameters, after analysis by the processor 830.

The memory 820 is configured to store a series of operating instructions that direct the operation of the processor 830 when initiated, including the code representing the one or more algorithms for analysis as disclosed herein. The one or more algorithms can correspond to a machine learning system, a rules-based system, and/or a numerical computation engine, wherein physics based computations can be used to infer new drilling parameters. The memory 820 can also store sensor data from a current drilling job, the previous well data, and/or statistical information derived from the previous well data. The memory 820 is a non-transitory computer readable medium.

The processor 830 is configured to execute the code and perform functions accordingly. The functions, for example, can be directing a drilling operation based on analysis of the previous and current well data, and or determining statistical information from previous well data. As such, the processor 830 includes the necessary logic to communicate with the interface 810 and the memory 820 and perform the functions described herein to execute an action.

A portion of the above-described apparatus, systems or methods may be embodied in or performed by various analog or digital data processors, wherein the processors are programmed or store executable programs of sequences of software instructions to perform one or more of the steps of the methods. A processor may be, for example, a programmable logic device such as a programmable array logic (PAL), a generic array logic (GAL), a field programmable gate arrays (FPGA), or another type of computer processing device (CPD). The software instructions of such programs may represent algorithms and be encoded in machine-executable form on non-transitory digital data storage media, e.g., magnetic or optical disks, random-access memory (RAM), magnetic hard disks, flash memories, and/or read-only memory (ROM), to enable various types of digital data processors or computers to perform one, multiple or all of the steps of one or more of the above-described methods, or functions, systems or apparatuses described herein.

Portions of disclosed examples or embodiments may relate to computer storage products with a non-transitory computer-readable medium that have program code thereon for performing various computer-implemented operations that embody a part of an apparatus, device or carry out the steps of a method set forth herein. Non-transitory used herein refers to all computer-readable media except for transitory, propagating signals. Examples of non-transitory computer-readable media include but are not limited to: magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROM disks; magneto-optical media such as floppy disks; and hardware devices that are specially configured to store and execute program code, such as ROM and RAM devices. Configured, or configured to, means, for example, designed, constructed, or programmed, with the necessary logic and/or features for performing a task or tasks. A configured device, therefore, is capable of performing the task or tasks. Examples of program code include both machine code, such as produced by a compiler, and files containing higher level code that may be executed by the computer using an interpreter.

In interpreting the disclosure, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced.

Those skilled in the art to which this application relates will appreciate that other and further additions, deletions, substitutions and modifications may be made to the described embodiments. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, because the scope of the present disclosure will be limited only by the claims. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present disclosure, a limited number of the example methods and materials are described herein.

Various aspects of the disclosure can be claimed including the apparatuses, systems, and methods disclosed herein. Aspects disclosed herein and noted in the Summary include:

A. A method of drilling a well, comprising: (1) deriving statistical information from data of previous wells that includes confidence intervals and one or more limiter overlays, wherein the previous well data includes rate of penetration (ROP) maps from bit rock models of the previous wells, (2) ascertaining drilling parameters for a current well using a bit rock model of the current well, (3) drilling the current well using the drilling parameters, (4) detecting a drilling challenge during the drilling of the current well, wherein drilling challenges occur when one of the drilling parameters is outside of a corresponding one of the confidence intervals, (5) applying, when determining one of the one or more limiter overlays corresponds to the drilling challenge, the corresponding one of the one or more limiter overlays, (6) identifying an action for the drilling of the current well according to the corresponding one of the one or more limiter overlays, and (7) continuing the drilling of the current well according to the action.

B. A drilling computing system comprising: (1) one or more memories having operating instructions for drilling a current well using statistical information from previous well data and drilling parameters ascertained from a bit rock model of the current well, wherein the statistical information includes one or more of limiter overlays and confidence intervals, and (2) one or more processors configured to perform operations according to the operating instructions, wherein the operations include (2A) detecting a drilling challenge during the drilling of the current well, wherein drilling challenges occur when one of the drilling parameters is outside of a corresponding one of the confidence intervals, (2B) applying, when determining one of the one or more limiter overlays corresponds to the drilling challenge, the corresponding one of the one or more limiter overlays, (2C) identifying an action for the drilling of the current well according to the corresponding one of the one or more limiter overlays, and (2D) continuing the drilling of the current well according to the action.

C. A well system for drilling a current well, comprising: (1) surface equipment and (2) one or more processors configured to perform operations including (2A) ascertaining drilling parameters for the current well using a bit rock model generated using surface data from the surface equipment, (2B) detecting a drilling challenge during drilling of the current well using the drilling parameters, wherein drilling challenges occur when one of the drilling parameters is outside of a confidence interval derived from previous well data, (2C) adjusting one or more of the drilling parameters according to at least one limiter overlay when the at least one limiter overlay corresponds to the drilling challenge, wherein the at least one limiter overlay is derived from the previous well data, and (2D) maintaining the drilling parameters when determining the limiter overlay does not correspond to the drilling challenge.

Each of aspects A, B, and C can have one or more of the following additional elements in combination: Element 1: continuing drilling the current well using the drilling parameters when determining one of the one or more limiter overlays does not correspond to the drilling challenge. Element 2: wherein detecting the drilling challenge is performed automatically. Element 3: wherein applying the corresponding one of the one or more limiter overlays is performed automatically. Element 4: wherein the action is one or more adjustments to the drilling parameters or one or more rig actions. Element 5: wherein the corresponding one of the limiter overlays is a challenge overlay that corresponds to an adverse condition and the drilling parameters associated therewith. Element 6: wherein the adverse condition includes one or more of: bit wear, stick slip, whirl, telemetry, geosteering, high frequency torsional oscillation, hole cleaning, washout, packoff, managed temperature drilling, stringer, and steering limitations. Element 7: wherein the action includes changing one or more of the drilling parameters. Element 8: wherein the drilling parameters include weight on bit (WOB), revolutions per minute (RPM), or rate of flow. Element 9: wherein the action is a wellbore action. Element 10: wherein the wellbore action includes cleaning the hole of the current well or replacing a drill bit being used for the drilling. Element 11: further comprising providing a real-time visualization of the drilling of the current well with respect to the statistical information from the previous well data. Element 12: wherein the confidence intervals are provided per a unit of depth, per stand, or per multiple stands. Element 13: wherein the operations further include continuing drilling the current well using the drilling parameters when determining one of the one or more limiter overlays does not correspond to the drilling challenge. Element 14: wherein the operating instructions correspond to machine learning algorithms, rules based algorithms, or algorithms of a numerical computation engine. Element 15: further comprising a screen, wherein the operations further include displaying a comparison of the drilling parameters to the statistical information from the previous well data. Element 16: wherein at least a portion of continuing the drilling is performed manually by an operator viewing the screen. Element 17: wherein the previous well data includes rate of penetration (ROP) maps of bit rock models of previous wells that were generated using surface data from the previous wells.