REAL TIME MAXIMUM HORIZONTAL STRESS CALIBRATION BASED ON PREDICTED CALIPER LOG WHILE DRILLING

Abstract

Systems and methods include a computer-method for updating drilling parameters in real time. A predicted breakout geometry is determined for a drilling operation of a petrochemical well. Determining the predicted breakout geometry uses an analytical elastic breakout model and includes determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle. The predicted breakout geometry is compared with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation. A maximum horizontal stress value in the analytical elastic breakout model is adjusted until the predicted breakout geometry matches the observed breakout geometry within a percentage threshold. Mud weight calculations for the drilling operation are updated in response to the comparing and adjusting. Drilling parameters for the drilling operation are changed in real time in response to the updating.

Description

TECHNICAL FIELD

The present disclosure applies to monitoring parameters and optimizing conditions while drilling, such as drilling an oil well.

BACKGROUND

Maximum horizontal stress is one of the most critical parameters affecting the stability of a wellbore during drilling operations. Conventional systems typically do not provide direct measurements to validate the magnitude of maximum horizontal stress. When no direct measurement can be verified, the industry relies on theoretical solutions, which adds uncertainty to field operations.

SUMMARY

The present disclosure describes techniques that can be used for correcting the maximum horizontal stress value in real time while drilling and subsequently accounting for its effect when calculating the optimum mud weight. In some implementations, a computer-implemented method includes the following. A predicted breakout geometry is determined for a drilling operation of a petrochemical well. Determining the predicted breakout geometry uses an analytical elastic breakout model and includes determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle. The predicted breakout geometry is compared with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation. A maximum horizontal stress value in the analytical elastic breakout model is adjusted until the predicted breakout geometry matches the observed breakout geometry within a percentage threshold. Mud weight calculations for the drilling operation are updated in response to the comparing and adjusting. Drilling parameters for the drilling operation are changed in real time in response to the updating.

The previously described implementation is implementable using a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer-implemented system including a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method, the instructions stored on the non-transitory, computer-readable medium.

The subject matter described in this specification can be implemented in particular implementations, so as to realize one or more of the following advantages. The magnitude of the maximum horizontal stress can be updated in real time while drilling. The term real-time can correspond to events that occur, for example, within a specified period of time, such as within a few seconds or a few minutes. This provides an advantage over conventional techniques that rely on equations to calculate the maximum horizontal stress when no direct measurement is available. Techniques can correct for the magnitude of maximum horizontal stress and subsequently provide updates to collapse and fracture mud weight pressure measurements. The techniques provide continuous measurements of breakout geometry and updates on the maximum horizontal stress. Corrected stress values can potentially be used in hydraulic fracturing applications.

The details of one or more implementations of the subject matter of this specification are set forth in the Detailed Description, the accompanying drawings, and the claims. Other features, aspects, and advantages of the subject matter will become apparent from the Detailed Description, the claims, and the accompanying drawings.

DESCRIPTION OF DRAWINGS

FIG. 1A is a diagram showing examples of a borehole breakout width/angle in conventional systems, according to some implementations of the present disclosure.

FIG. 1B includes a graph showing consistence in a theoretical plot and an experimental plot of breakout width, according to some implementations of the present disclosure.

FIG. 2 is a diagram of an example of a graph showing examples of breakout and in-situ stresses of a borehole in conventional systems, according to some implementations of the present disclosure.

FIG. 3 is a diagram showing an example of an elastic breakout model prediction, according to some implementations of the present disclosure.

FIG. 4 is a diagram showing an example of a process for modifying and correcting the magnitude of the maximum horizontal stress, according to some implementations of the present disclosure.

FIG. 5 is a graph showing an example of a caliper log without the calibration of maximum horizontal stress, according to some implementations of the present disclosure.

FIG. 6 is a graph showing an example of a caliper log with the calibration of maximum horizontal stress, according to some implementations of the present disclosure.

FIG. 7 is a screen print showing an example of a mud weight window using original maximum horizontal stress, according to some implementations of the present disclosure.

FIG. 8 is a screen print showing an example of the mud weight window using a 5% increase in maximum horizontal stress, according to some implementations of the present disclosure.

FIG. 9 is a flowchart of an example of a method for performing real-time maximum horizontal stress calibration based on a predicted caliper log while drilling, according to some implementations of the present disclosure.

FIG. 10 is a block diagram illustrating an example computer system used to provide computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures as described in the present disclosure, according to some implementations of the present disclosure.

Like reference numbers and designations in the various drawings indicate like elements.

DETAILED DESCRIPTION

The following detailed description describes techniques for correcting the maximum horizontal stress value in real time while drilling and subsequently accounting for its effect when calculating the optimum mud weight. This includes calibrating the magnitude of maximum horizontal stress in real time while drilling, which is critical for optimizing mud weight during drilling. The term real-time can correspond to events that occur, for example, within a specified period of time, such as within a few seconds or a few minutes. Various modifications, alterations, and permutations of the disclosed implementations can be made and will be readily apparent to those of ordinary skill in the art, and the general principles defined may be applied to other implementations and applications, without departing from scope of the disclosure. In some instances, details unnecessary to obtain an understanding of the described subject matter may be omitted so as to not obscure one or more described implementations with unnecessary detail and inasmuch as such details are within the skill of one of ordinary skill in the art. The present disclosure is not intended to be limited to the described or illustrated implementations, but to be accorded the widest scope consistent with the described principles and features.

Conventional systems do not provide a direct measurement of the maximum horizontal stress to validate its magnitude while drilling. The techniques of the present disclosure provide for a calibration of the maximum horizontal stress in real-time, including determining the maximum horizontal stress from equations using to minimum horizontal stress (σ_h) and vertical stress (σ_V). The term real-time can correspond to events that occur, for example, within a specified period of time, such as within a few seconds or a few minutes. The maximum horizontal stress can be calibrated based on the predicted caliper log while drilling. The maximum horizontal stress magnitude can be corrected based on the breakout’s width recorded in the real time caliper log. The maximum horizontal stress magnitude can be adjusted until convergence occurs the breakout’s width on the predicted caliper and real-time caliper log. The modified value of the maximum horizontal stress can then be used to re-calculated the mud weights.

FIG. 1A is a diagram showing an example 100 of a borehole breakout width/angle in conventional systems, according to some implementations of the present disclosure. It is well observed and accepted that the borehole breakout width/angle is expected to remain stable after the initiation even though the breakout depth 102 may continue to grow, as shown in FIG. 1A. For this reason, breakout width/angle of a borehole 104 is often used to reversely calculate the maximum horizontal stress (for example, in vertical wells). FIG. 1B includes a graph 150 showing consistence in a theoretical plot 152 and an experimental plot 154 of breakout width, according to some implementations of the present disclosure. In FIG. 1B, the maximum horizontal stress σ_Hmax is shown in a y- direction and the minimum horizontal stress is shown in a x-direction; θ_b is the breakout width/angle with center at x-axis]. Axis 156 shows the magnitude of the maximum horizontal stress σ_Hmax. Axis 158 shows the corresponding breakout width/angles (θ_b) at different maximum horizontal stress (σ_Hmax), relative to equation 160.

FIG. 2 is a diagram of an example of a graph 200 showing examples of breakout and in-situ stresses of a borehole in conventional systems, according to some implementations of the present disclosure. For example, the following equation can be used to back-calculate the maximum horizontal stress from the breakout width/angle:

${\sigma }_{Hmax}=\frac{ucs+\text{Δ}{P}_W+2P_p}{1-2\cos 2{\theta }_b}-{\sigma }_{hmin}\frac{1+2\cos 2{\theta }_b}{1-2\cos 2{\theta }_b}$

where ucs is the unconfined compressive strength; (σ_H and (σ_h are the maximum and minimum horizontal stresses 202 and 204, respectively; θ_b 206 is the wellbore angle measured from the maximum horizontal stress direction where the breakout starts; P_p is the formation pore pressure; and ΔP_W is the wellbore pressure above the formation pore pressure, as per equation 210. θ_b is an angle 208 measured from the minimum horizontal stress to the edge of breakout; and P_w is a wellbore pressure 210.

FIG. 3 is a diagram showing an example of an elastic breakout model prediction 300, according to some implementations of the present disclosure. Crescent-shaped areas 302 represent a predicted breakout region. In this example, φ_bo is a predicted breakout angle 304 in degrees, and d_bo is a predicted caliper 306 (for example, 0.24 meters (m)). A drill bit diameter used for the elastic breakout model prediction 300 can be 0.2 m, for example. The elastic breakout model prediction 300 is plotted relative to a maximum horizontal stress (SH_max) 308 and a minimum horizontal stress (SH_min) 310.

FIG. 4 is a diagram showing an example of a process 400 for modifying and correcting the magnitude of the maximum horizontal stress, according to some implementations of the present disclosure. The process 400 can be used in real-time while drilling vertical, horizontal, or inclined wells, for example.

At step 402, breakout geometry is predicted using an analytical or numerical model, including predicting a breakout angle (or breakout width) and a breakout depth (with constitutive behavior of the rock known). For example, caliper data can be predicted using poroelastoplastic models. In this first step, input data 410 can be used that includes parameters such as a pore pressure, a minimum horizontal stress azimuth, and a tensile strength. The step can also use the maximum horizontal stress (σ_h), maximum vertical stress (σ_V), a cohesion friction angle UCS, and a Young Modulus Poisson’s ratio for horizontal wells which are typically drilled in the direction of minimum horizontal stress direction. The model uses the geomechanical properties from the 1D Mechanical Earth Model (MEM) , the constitutive behavior of the formation measured in the rock mechanics lab, as well as real-time data including equivalent circulating density (ECD) which can be converted into well pressure. The model can use any of the existing analytical solutions or solutions given by numerical models for computing effective stresses in combination with any of the shear failure criteria. Examples of analytical solutions for effective stresses include various elastic solutions and poroelastic solutions well-known to the industry. Examples of shear failure criteria include Mohr-Coulomb, Drucker-Prager, modified Lade, and Mogi-Coulomb techniques. FIG. 3 illustrates a breakout prediction using an elastic solution in combination with the Mohr-Coulomb criterion, for example. A result of the first step is an initial estimation of σ_H.

At step 404 includes comparing the real-time caliper log data (observed breakout’s depth and angle, for example) with a multi-finger caliper while drilling. This includes comparing a breakout’s depth observed in real time with a predicted breakout depth. Real-time caliper data 414 obtained from a data link 412 can be used in the calculations.

Assuming all of the rock properties that were used in the calculation of the predicted caliper were verified except for the maximum horizontal stress, At step 406 includes adjusting the maximum horizontal stress value in the breakout model until the predicted breakout geometry matches the one observed from the real-time caliper log data. For example, adjusting the maximum horizontal stress value can include making adjustments until matching is within a threshold, for example, 5% or less. Matching can be done by comparing only the breakout depth, or only the breakout angle, or both. By modifying the maximum horizontal stress magnitude in real-time to match the observed breakout geometry, a more accurate representation of the magnitude of the maximum horizontal stress can be obtained. The maximum horizontal stress of 1D mechanical earth modeling (1D MEM) (the numerical representation of rock mechanical properties and the state of in situ stresses along a borehole) can be updated in real-time, and the corrected values can be used to re-calculate the optimum mud weight while drilling.

If at step 406, convergence has not occurred, then at step 416 the predicted breakout depth is adjusted by an adjustment percentage (for example, 1%). If the predicted break-out depth is greater than the real-time break-out depth, then the predicted break-out depth can be decreased by 1%. Otherwise, if the predicted break-out depth is less than the real-time break-out depth, then the predicted break-out depth can be increased by 1%. Then processing can proceed to step 408.

At 408, mud weight calculations are updated using a corrected σ_H. The updated mud weight calculations can be used during drilling operations, for example, to make real-time changes in drilling parameters.

The maximum horizontal stress is one of the critical parameters in the 1D MEM that has a huge impact when calculating the critical collapse and fracture gradients. The maximum horizontal stress affects the mud weight window and the stability of the wellbore (as described with reference to FIGS. 7 and 8).

FIG. 5 is a graph showing an example of a caliper log 500 without the calibration of maximum horizontal stress, according to some implementations of the present disclosure. The graph 500 includes a real-time caliper plot 502 and an uncorrected maximum horizontal stress plot 504. The plots 502 and 504 are plotted relative to a caliper-measured borehole size 506 (for example, in inches) and a well depth 508 (for example, in feet).

FIG. 6 is a graph showing an example of a caliper log 600 with the calibration of maximum horizontal stress, according to some implementations of the present disclosure. The graph 600 includes a real-time caliper plot 602 and an corrected maximum horizontal stress plot 604. The plots 602 and 604 are plotted relative to a caliper-measured borehole size 606 (for example, in inches) and a well depth 608 (for example, in feet).

FIG. 7 is a screen print showing an example of a mud weight window 700 using original maximum horizontal stress, according to some implementations of the present disclosure. The mud weight window 700 includes plots of a collapse gradient 702, a fracture gradient 704, a stable gradient 706, a pore pressure 708, a minimum horizontal stress 710, a fracture mud weight (MW) 712, and a collapse mud weight 714. Elements of the mud weight window 700 are plotted relative to a wellbore inclination angle 716 (for example, in degrees) and a drilling mud weight 718 (for example, in pounds per cubic foot (pcf)).

In this example, the input summary 720 includes the following, for example. Analysis settings identify an elastic model (for example, no time involved), a borehole condition (for example, “impermeable”), and a radial ratio without breakout (for example, 1). Wellbore geometry information includes a true vertical depth (TVD) of 13,284 feet, a borehole radius of 0.24 feet, an average inclination of 87.49 degrees, and an average azimuth of 173.43 degrees. In situ stresses and pore pressure include an overburden stress gradient of 21.78 pounds per gallon (ppg), a maximum horizontal stress gradient of 27.54 ppg, a minimum horizontal stress gradient of 18.13 ppg, a pore pressure gradient of 10.15, and a maximum horizontal stress azimuth of 75 degrees. Elastic properties include a Young’s Modulus of 7.94 megapounds per square inch (Mpsi) and a Poisson’s ratio of 0.23. Failure criteria and strength properties include a failure condition (for example, Mohr-Coulomb), a cohesion of 2,342.15 pounds per square inch (psi), a friction angle of 42.83 degrees, and a tensile strength of 536.17 psi.

FIG. 8 is a screen print showing an example of the mud weight window using a 5% increase in maximum horizontal stress, according to some implementations of the present disclosure. The elements plotted in FIG. 8 are plotted differently than in FIG. 7.

An input summary 720, which can be displayed on the mud weight window 700, identifies specific inputs to the mud weight window 700, including the following, for example. Analysis settings identify an elastic model (for example, no time involved), a borehole condition (for example, “impermeable”), and a radial ratio without breakout (for example, 1). Wellbore geometry information includes a TVD of 13,284 feet, a borehole radius of 0.24 feet, an average inclination of 87.49 degrees, and an average azimuth of 173.43 degrees. In situ stresses and pore pressure include an overburden stress gradient of 21.78 ppg, a maximum horizontal stress gradient of 26.11 ppg, a minimum horizontal stress gradient of 18.13 ppg, a pore pressure gradient of 10.15, and a maximum horizontal stress azimuth of 75 degrees. Elastic properties include a Young’s Modulus of 7.94 Mpsi and a Poisson’s ratio of 0.23. Failure criteria and strength properties include a failure condition (for example, Mohr-Coulomb), a cohesion of 2,342.15 psi, a friction angle of 42.83 degrees, and a tensile strength of 536.17 psi.

FIG. 9 is a flowchart of an example of a method 900 for performing real-time maximum horizontal stress calibration based on a predicted caliper log while drilling, according to some implementations of the present disclosure. For clarity of presentation, the description that follows generally describes method 900 in the context of the other figures in this description. However, it will be understood that method 900 can be performed, for example, by any suitable system, environment, software, and hardware, or a combination of systems, environments, software, and hardware, as appropriate. In some implementations, various steps of method 900 can be run in parallel, in combination, in loops, or in any order.

At 902, a predicted breakout geometry is determined for a drilling operation of a petrochemical well. Determining the predicted breakout geometry uses an analytical elastic breakout model and includes determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle. For example, determining the predicted breakout geometry can be based on a pore pressure, a maximum horizontal stress azimuth, a tensile strength, a maximum horizontal stress (σ_h), a maximum vertical stress (σ_V), a cohesion friction angle UCS, and a Young Modulus Poisson’s ratio. In some implementations, the analytical elastic breakout model can use geomechanical properties from a one-dimensional (1D) Mechanical Earth Model (MEM) and real-time data including an equivalent circulating density (ECD). The analytical elastic breakout model can support computing effective stresses in combination with shear failure criteria. For example, computing the effective stresses can include computing various elastic solutions and poroelastic solutions. The shear failure criteria can include Mohr-Coulomb, Drucker-Prager, modified Lade, and Mogi-Coulomb techniques, for example. From 902, method 900 proceeds to 904.

At 904, the predicted breakout geometry is compared with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation. As an example, a breakout angle can be predicted in the breakout region of the crescent-shaped areas 302, as described with reference to FIG. 3. From 904, method 900 proceeds to 906.

At 906, a maximum horizontal stress value in the analytical elastic breakout model is adjusted until the predicted breakout geometry matches the observed breakout geometry within a percentage threshold. For example, adjusting the maximum horizontal stress value in the analytical elastic breakout model can include incrementally adjusting the predicted breakout depth by 1%. From 906, method 900 proceeds to 908.

At 908, mud weight calculations for the drilling operation are updated in response to the comparing and adjusting. For example, mud weight calculations can be corrected as part of the process 400 which is described with reference to FIG. 4. From 908, method 900 proceeds to 910.

At 910, drilling parameters for the drilling operation are changed in real time in response to the updating. For example, systems used to control drilling equipment can be provided with updated parameters based on suggested changes. After 910, method 900 can stop.

In some implementations, in addition to (or in combination with) any previously-described features, techniques of the present disclosure can include the following. Customized user interfaces can present intermediate or final results of the above described processes to a user. The presented information can be presented in one or more of textual, tabular, or graphical format, such as through a dashboard. The information can be presented at one or more of on-site locations (such as at an oil well or other facility), on the Internet (such as on a webpage), on a mobile application (or “app”), or at a central processing facility. The presented information can include suggestions, such as suggested changes in parameters or processing inputs, that the user can select to implement improvements in a production environment, such as in the exploration, production, and/or testing of petrochemical processes or facilities. For example, the suggestions can include parameters that, when selected by the user, can cause a change or an improvement in drilling parameters (including speed and direction) or overall production of a gas or oil well. The suggestions, when implemented by the user, can improve the speed and accuracy of calculations, streamline processes, improve models, and solve problems related to efficiency, performance, safety, reliability, costs, downtime, and the need for human interaction. In some implementations, the suggestions can be implemented in real-time, such as to provide an immediate or near-immediate change in operations or in a model. The term real-time can correspond, for example, to events that occur within a specified period of time, such as within one minute or within one second. In some implementations, values of parameters or other variables that are determined can be used automatically (such as through using rules) to implement changes in oil or gas well exploration, production/drilling, or testing. For example, outputs of the present disclosure can be used as inputs to other equipment and/or systems at a facility. This can be especially useful for systems or various pieces of equipment that are located several meters or several miles apart, or are located in different countries or other jurisdictions.

FIG. 10 is a block diagram of an example computer system 1000 used to provide computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures described in the present disclosure, according to some implementations of the present disclosure. The illustrated computer 1002 is intended to encompass any computing device such as a server, a desktop computer, a laptop/notebook computer, a wireless data port, a smart phone, a personal data assistant (PDA), a tablet computing device, or one or more processors within these devices, including physical instances, virtual instances, or both. The computer 1002 can include input devices such as keypads, keyboards, and touch screens that can accept user information. Also, the computer 1002 can include output devices that can convey information associated with the operation of the computer 1002. The information can include digital data, visual data, audio information, or a combination of information. The information can be presented in a graphical user interface (UI) (or GUI).

The computer 1002 can serve in a role as a client, a network component, a server, a database, a persistency, or components of a computer system for performing the subject matter described in the present disclosure. The illustrated computer 1002 is communicably coupled with a network 1030. In some implementations, one or more components of the computer 1002 can be configured to operate within different environments, including cloud-computing-based environments, local environments, global environments, and combinations of environments.

At a top level, the computer 1002 is an electronic computing device operable to receive, transmit, process, store, and manage data and information associated with the described subject matter. According to some implementations, the computer 1002 can also include, or be communicably coupled with, an application server, an email server, a web server, a caching server, a streaming data server, or a combination of servers.

The computer 1002 can receive requests over network 1030 from a client application (for example, executing on another computer 1002). The computer 1002 can respond to the received requests by processing the received requests using software applications. Requests can also be sent to the computer 1002 from internal users (for example, from a command console), external (or third) parties, automated applications, entities, individuals, systems, and computers.

Each of the components of the computer 1002 can communicate using a system bus 1003. In some implementations, any or all of the components of the computer 1002, including hardware or software components, can interface with each other or the interface 1004 (or a combination of both) over the system bus 1003. Interfaces can use an application programming interface (API) 1012, a service layer 1013, or a combination of the API 1012 and service layer 1013. The API 1012 can include specifications for routines, data structures, and object classes. The API 1012 can be either computer-language independent or dependent. The API 1012 can refer to a complete interface, a single function, or a set of APIs.

The service layer 1013 can provide software services to the computer 1002 and other components (whether illustrated or not) that are communicably coupled to the computer 1002. The functionality of the computer 1002 can be accessible for all service consumers using this service layer. Software services, such as those provided by the service layer 1013, can provide reusable, defined functionalities through a defined interface. For example, the interface can be software written in JAVA, C++, or a language providing data in extensible markup language (XML) format. While illustrated as an integrated component of the computer 1002, in alternative implementations, the API 1012 or the service layer 1013 can be stand-alone components in relation to other components of the computer 1002 and other components communicably coupled to the computer 1002. Moreover, any or all parts of the API 1012 or the service layer 1013 can be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of the present disclosure.

The computer 1002 includes an interface 1004. Although illustrated as a single interface 1004 in FIG. 10, two or more interfaces 1004 can be used according to particular needs, desires, or particular implementations of the computer 1002 and the described functionality. The interface 1004 can be used by the computer 1002 for communicating with other systems that are connected to the network 1030 (whether illustrated or not) in a distributed environment. Generally, the interface 1004 can include, or be implemented using, logic encoded in software or hardware (or a combination of software and hardware) operable to communicate with the network 1030. More specifically, the interface 1004 can include software supporting one or more communication protocols associated with communications. As such, the network 1030 or the interface’s hardware can be operable to communicate physical signals within and outside of the illustrated computer 1002.

The computer 1002 includes a processor 1005. Although illustrated as a single processor 1005 in FIG. 10, two or more processors 1005 can be used according to particular needs, desires, or particular implementations of the computer 1002 and the described functionality. Generally, the processor 1005 can execute instructions and can manipulate data to perform the operations of the computer 1002, including operations using algorithms, methods, functions, processes, flows, and procedures as described in the present disclosure.

The computer 1002 also includes a database 1006 that can hold data for the computer 1002 and other components connected to the network 1030 (whether illustrated or not). For example, database 1006 can be an in-memory, conventional, or a database storing data consistent with the present disclosure. In some implementations, database 1006 can be a combination of two or more different database types (for example, hybrid in-memory and conventional databases) according to particular needs, desires, or particular implementations of the computer 1002 and the described functionality. Although illustrated as a single database 1006 in FIG. 10, two or more databases (of the same, different, or combination of types) can be used according to particular needs, desires, or particular implementations of the computer 1002 and the described functionality. While database 1006 is illustrated as an internal component of the computer 1002, in alternative implementations, database 1006 can be external to the computer 1002.

The computer 1002 also includes a memory 1007 that can hold data for the computer 1002 or a combination of components connected to the network 1030 (whether illustrated or not). Memory 1007 can store any data consistent with the present disclosure. In some implementations, memory 1007 can be a combination of two or more different types of memory (for example, a combination of semiconductor and magnetic storage) according to particular needs, desires, or particular implementations of the computer 1002 and the described functionality. Although illustrated as a single memory 1007 in FIG. 10, two or more memories 1007 (of the same, different, or combination of types) can be used according to particular needs, desires, or particular implementations of the computer 1002 and the described functionality. While memory 1007 is illustrated as an internal component of the computer 1002, in alternative implementations, memory 1007 can be external to the computer 1002.

The application 1008 can be an algorithmic software engine providing functionality according to particular needs, desires, or particular implementations of the computer 1002 and the described functionality. For example, application 1008 can serve as one or more components, modules, or applications. Further, although illustrated as a single application 1008, the application 1008 can be implemented as multiple applications 1008 on the computer 1002. In addition, although illustrated as internal to the computer 1002, in alternative implementations, the application 1008 can be external to the computer 1002.

The computer 1002 can also include a power supply 1014. The power supply 1014 can include a rechargeable or non-rechargeable battery that can be configured to be either user- or non-user-replaceable. In some implementations, the power supply 1014 can include power-conversion and management circuits, including recharging, standby, and power management functionalities. In some implementations, the power-supply 1014 can include a power plug to allow the computer 1002 to be plugged into a wall socket or a power source to, for example, power the computer 1002 or recharge a rechargeable battery.

There can be any number of computers 1002 associated with, or external to, a computer system containing computer 1002, with each computer 1002 communicating over network 1030. Further, the terms “client,” “user,” and other appropriate terminology can be used interchangeably, as appropriate, without departing from the scope of the present disclosure. Moreover, the present disclosure contemplates that many users can use one computer 1002 and one user can use multiple computers 1002.

Described implementations of the subject matter can include one or more features, alone or in combination.

For example, in a first implementation, a computer-implemented method includes the following. A predicted breakout geometry is determined for a drilling operation of a petrochemical well. Determining the predicted breakout geometry uses an analytical elastic breakout model and includes determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle. The predicted breakout geometry is compared with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation. A maximum horizontal stress value in the analytical elastic breakout model is adjusted until the predicted breakout geometry matches the observed breakout geometry within a percentage threshold. Mud weight calculations for the drilling operation are updated in response to the comparing and adjusting. Drilling parameters for the drilling operation are changed in real time in response to the updating.

The foregoing and other described implementations can each, optionally, include one or more of the following features:

A first feature, combinable with any of the following features, where determining the predicted breakout geometry is based on a pore pressure, a maximum horizontal stress azimuth, a tensile strength, a maximum horizontal stress (σ_h), a maximum vertical stress (σ_V), a cohesion friction angle UCS, and a Young Modulus Poisson’s ratio.

A second feature, combinable with any of the previous or following features, where the analytical elastic breakout model uses geomechanical properties from a one-dimensional (1D) Mechanical Earth Model (MEM) and real-time data including an equivalent circulating density (ECD).

A third feature, combinable with any of the previous or following features, where the analytical elastic breakout model supports computing effective stresses in combination with shear failure criteria.

A fourth feature, combinable with any of the previous or following features, where computing the effective stresses includes computing various elastic solutions and poroelastic solutions.

A fifth feature, combinable with any of the previous or following features, where the shear failure criteria include Mohr-Coulomb, Drucker-Prager, modified Lade, and Mogi-Coulomb techniques.

A sixth feature, combinable with any of the previous or following features, where adjusting the maximum horizontal stress value in the analytical elastic breakout model includes incrementally adjusting the predicted breakout depth by 1%.

In a second implementation, a non-transitory, computer-readable medium stores one or more instructions executable by a computer system to perform operations including the following. A predicted breakout geometry is determined for a drilling operation of a petrochemical well. Determining the predicted breakout geometry uses an analytical elastic breakout model and includes determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle. The predicted breakout geometry is compared with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation. A maximum horizontal stress value in the analytical elastic breakout model is adjusted until the predicted breakout geometry matches the observed breakout geometry within a percentage threshold. Mud weight calculations for the drilling operation are updated in response to the comparing and adjusting. Drilling parameters for the drilling operation are changed in real time in response to the updating.

The foregoing and other described implementations can each, optionally, include one or more of the following features:

A first feature, combinable with any of the following features, where determining the predicted breakout geometry is based on a pore pressure, a maximum horizontal stress azimuth, a tensile strength, a maximum horizontal stress (σ_h), a maximum vertical stress (σ_V), a cohesion friction angle UCS, and a Young Modulus Poisson’s ratio.

A second feature, combinable with any of the previous or following features, where the analytical elastic breakout model uses geomechanical properties from a one-dimensional (1D) Mechanical Earth Model (MEM) and real-time data including an equivalent circulating density (ECD).

A third feature, combinable with any of the previous or following features, where the analytical elastic breakout model supports computing effective stresses in combination with shear failure criteria.

A fourth feature, combinable with any of the previous or following features, where computing the effective stresses includes computing various elastic solutions and poroelastic solutions.

A fifth feature, combinable with any of the previous or following features, where the shear failure criteria include Mohr-Coulomb, Drucker-Prager, modified Lade, and Mogi-Coulomb techniques.

A sixth feature, combinable with any of the previous or following features, where adjusting the maximum horizontal stress value in the analytical elastic breakout model includes incrementally adjusting the predicted breakout depth by 1%.

In a third implementation, a computer-implemented system includes one or more processors and a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors. The programming instructions instruct the one or more processors to perform operations including the following. A predicted breakout geometry is determined for a drilling operation of a petrochemical well. Determining the predicted breakout geometry uses an analytical elastic breakout model and includes determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle. The predicted breakout geometry is compared with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation. A maximum horizontal stress value in the analytical elastic breakout model is adjusted until the predicted breakout geometry matches the observed breakout geometry within a percentage threshold. Mud weight calculations for the drilling operation are updated in response to the comparing and adjusting. Drilling parameters for the drilling operation are changed in real time in response to the updating.

The foregoing and other described implementations can each, optionally, include one or more of the following features:

A first feature, combinable with any of the following features, where determining the predicted breakout geometry is based on a pore pressure, a maximum horizontal stress azimuth, a tensile strength, a maximum horizontal stress (σ_h), a maximum vertical stress (σ_V), a cohesion friction angle UCS, and a Young Modulus Poisson’s ratio.

A second feature, combinable with any of the previous or following features, where the analytical elastic breakout model uses geomechanical properties from a one-dimensional (1D) Mechanical Earth Model (MEM) and real-time data including an equivalent circulating density (ECD).

A third feature, combinable with any of the previous or following features, where the analytical elastic breakout model supports computing effective stresses in combination with shear failure criteria.

A fourth feature, combinable with any of the previous or following features, where computing the effective stresses includes computing various elastic solutions and poroelastic solutions.

A fifth feature, combinable with any of the previous or following features, where the shear failure criteria include Mohr-Coulomb, Drucker-Prager, modified Lade, and Mogi-Coulomb techniques.

Implementations of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, in tangibly embodied computer software or firmware, in computer hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Software implementations of the described subject matter can be implemented as one or more computer programs. Each computer program can include one or more modules of computer program instructions encoded on a tangible, non-transitory, computer-readable computer-storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively, or additionally, the program instructions can be encoded in/on an artificially generated propagated signal. For example, the signal can be a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to a suitable receiver apparatus for execution by a data processing apparatus. The computer-storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of computer-storage mediums.

The terms “data processing apparatus,” “computer,” and “electronic computer device” (or equivalent as understood by one of ordinary skill in the art) refer to data processing hardware. For example, a data processing apparatus can encompass all kinds of apparatuses, devices, and machines for processing data, including by way of example, a programmable processor, a computer, or multiple processors or computers. The apparatus can also include special purpose logic circuitry including, for example, a central processing unit (CPU), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). In some implementations, the data processing apparatus or special purpose logic circuitry (or a combination of the data processing apparatus or special purpose logic circuitry) can be hardware- or software-based (or a combination of both hardware- and software-based). The apparatus can optionally include code that creates an execution environment for computer programs, for example, code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments. The present disclosure contemplates the use of data processing apparatuses with or without conventional operating systems, such as LINUX, UNIX, WINDOWS, MAC OS, ANDROID, or IOS.

A computer program, which can also be referred to or described as a program, software, a software application, a module, a software module, a script, or code, can be written in any form of programming language. Programming languages can include, for example, compiled languages, interpreted languages, declarative languages, or procedural languages. Programs can be deployed in any form, including as stand-alone programs, modules, components, subroutines, or units for use in a computing environment. A computer program can, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data, for example, one or more scripts stored in a markup language document, in a single file dedicated to the program in question, or in multiple coordinated files storing one or more modules, sub-programs, or portions of code. A computer program can be deployed for execution on one computer or on multiple computers that are located, for example, at one site or distributed across multiple sites that are interconnected by a communication network. While portions of the programs illustrated in the various figures may be shown as individual modules that implement the various features and functionality through various objects, methods, or processes, the programs can instead include a number of sub-modules, third-party services, components, and libraries. Conversely, the features and functionality of various components can be combined into single components as appropriate. Thresholds used to make computational determinations can be statically, dynamically, or both statically and dynamically determined.

The methods, processes, or logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output. The methods, processes, or logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, for example, a CPU, an FPGA, or an ASIC.

Computers suitable for the execution of a computer program can be based on one or more of general and special purpose microprocessors and other kinds of CPUs. The elements of a computer are a CPU for performing or executing instructions and one or more memory devices for storing instructions and data. Generally, a CPU can receive instructions and data from (and write data to) a memory.

Graphics processing units (GPUs) can also be used in combination with CPUs. The GPUs can provide specialized processing that occurs in parallel to processing performed by CPUs. The specialized processing can include artificial intelligence (AI) applications and processing, for example. GPUs can be used in GPU clusters or in multi-GPU computing.

A computer can include, or be operatively coupled to, one or more mass storage devices for storing data. In some implementations, a computer can receive data from, and transfer data to, the mass storage devices including, for example, magnetic, magneto-optical disks, or optical disks. Moreover, a computer can be embedded in another device, for example, a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive.

Computer-readable media (transitory or non-transitory, as appropriate) suitable for storing computer program instructions and data can include all forms of permanent/non-permanent and volatile/non-volatile memory, media, and memory devices. Computer-readable media can include, for example, semiconductor memory devices such as random access memory (RAM), read-only memory (ROM), phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices. Computer-readable media can also include, for example, magnetic devices such as tape, cartridges, cassettes, and internal/removable disks. Computer-readable media can also include magneto-optical disks and optical memory devices and technologies including, for example, digital video disc (DVD), CD-ROM, DVD+/-R, DVD-RAM, DVD-ROM, HD-DVD, and BLU-RAY. The memory can store various objects or data, including caches, classes, frameworks, applications, modules, backup data, jobs, web pages, web page templates, data structures, database tables, repositories, and dynamic information. Types of objects and data stored in memory can include parameters, variables, algorithms, instructions, rules, constraints, and references. Additionally, the memory can include logs, policies, security or access data, and reporting files. The processor and the memory can be supplemented by, or incorporated into, special purpose logic circuitry.

Implementations of the subject matter described in the present disclosure can be implemented on a computer having a display device for providing interaction with a user, including displaying information to (and receiving input from) the user. Types of display devices can include, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), a light-emitting diode (LED), and a plasma monitor. Display devices can include a keyboard and pointing devices including, for example, a mouse, a trackball, or a trackpad. User input can also be provided to the computer through the use of a touchscreen, such as a tablet computer surface with pressure sensitivity or a multi-touch screen using capacitive or electric sensing. Other kinds of devices can be used to provide for interaction with a user, including to receive user feedback including, for example, sensory feedback including visual feedback, auditory feedback, or tactile feedback. Input from the user can be received in the form of acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to, and receiving documents from, a device that the user uses. For example, the computer can send web pages to a web browser on a user’s client device in response to requests received from the web browser.

The term “graphical user interface,” or “GUI,” can be used in the singular or the plural to describe one or more graphical user interfaces and each of the displays of a particular graphical user interface. Therefore, a GUI can represent any graphical user interface, including, but not limited to, a web browser, a touch-screen, or a command line interface (CLI) that processes information and efficiently presents the information results to the user. In general, a GUI can include a plurality of user interface (UI) elements, some or all associated with a web browser, such as interactive fields, pull-down lists, and buttons. These and other UI elements can be related to or represent the functions of the web browser.

Implementations of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, for example, as a data server, or that includes a middleware component, for example, an application server. Moreover, the computing system can include a front-end component, for example, a client computer having one or both of a graphical user interface or a Web browser through which a user can interact with the computer. The components of the system can be interconnected by any form or medium of wireline or wireless digital data communication (or a combination of data communication) in a communication network. Examples of communication networks include a local area network (LAN), a radio access network (RAN), a metropolitan area network (MAN), a wide area network (WAN), Worldwide Interoperability for Microwave Access (WIMAX), a wireless local area network (WLAN) (for example, using 802.11 a/b/g/n or 802.20 or a combination of protocols), all or a portion of the Internet, or any other communication system or systems at one or more locations (or a combination of communication networks). The network can communicate with, for example, Internet Protocol (IP) packets, frame relay frames, asynchronous transfer mode (ATM) cells, voice, video, data, or a combination of communication types between network addresses.

The computing system can include clients and servers. A client and server can generally be remote from each other and can typically interact through a communication network. The relationship of client and server can arise by virtue of computer programs running on the respective computers and having a client-server relationship.

Cluster file systems can be any file system type accessible from multiple servers for read and update. Locking or consistency tracking may not be necessary since the locking of exchange file system can be done at application layer. Furthermore, Unicode data files can be different from non-Unicode data files.

While this specification contains many specific implementation details, these should not be construed as limitations on the scope of what may be claimed, but rather as descriptions of features that may be specific to particular implementations. Certain features that are described in this specification in the context of separate implementations can also be implemented, in combination, in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations, separately, or in any suitable sub-combination. Moreover, although previously described features may be described as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can, in some cases, be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.

Particular implementations of the subject matter have been described. Other implementations, alterations, and permutations of the described implementations are within the scope of the following claims as will be apparent to those skilled in the art. While operations are depicted in the drawings or claims in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed (some operations may be considered optional), to achieve desirable results. In certain circumstances, multitasking or parallel processing (or a combination of multitasking and parallel processing) may be advantageous and performed as deemed appropriate.

Moreover, the separation or integration of various system modules and components in the previously described implementations should not be understood as requiring such separation or integration in all implementations. It should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

Accordingly, the previously described example implementations do not define or constrain the present disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of the present disclosure.

Furthermore, any claimed implementation is considered to be applicable to at least a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer system including a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method or the instructions stored on the non-transitory, computer-readable medium.

Claims

1. A computer-implemented method, comprising:

determining, using an analytical elastic breakout model, a predicted breakout geometry, including determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle for a drilling operation of a petrochemical well;

comparing the predicted breakout geometry with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation;

adjusting a maximum horizontal stress value in the analytical elastic breakout model until the predicted breakout geometry matches, within a percentage threshold, the observed breakout geometry;

updating, in response to the comparing and adjusting, mud weight calculations for the drilling operation; and

changing, in real time and in response to the updating, drilling parameters for the drilling operation.

2. The computer-implemented method of claim 1, wherein determining the predicted breakout geometry is based on a pore pressure, a maximum horizontal stress azimuth, a tensile strength, a maximum horizontal stress (σh), a maximum vertical stress (σV), a cohesion friction angle UCS, and a Young Modulus Poisson’s ratio.

3. The computer-implemented method of claim 1, wherein the analytical elastic breakout model uses geomechanical properties from a one-dimensional (1D) Mechanical Earth Model (MEM) and real-time data including an equivalent circulating density (ECD).

4. The computer-implemented method of claim 1, wherein the analytical elastic breakout model supports computing effective stresses in combination with shear failure criteria.

5. The computer-implemented method of claim 4, wherein computing the effective stresses includes computing various elastic solutions and poroelastic solutions.

6. The computer-implemented method of claim 4, wherein the shear failure criteria include Mohr-Coulomb, Drucker-Prager, modified Lade, and Mogi-Coulomb techniques.

7. The computer-implemented method of claim 1, wherein adjusting the maximum horizontal stress value in the analytical elastic breakout model includes incrementally adjusting the predicted breakout depth by 1%.

8. A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

determining, using an analytical elastic breakout model, a predicted breakout geometry, including determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle for a drilling operation of a petrochemical well;

comparing the predicted breakout geometry with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation;

adjusting a maximum horizontal stress value in the analytical elastic breakout model until the predicted breakout geometry matches, within a percentage threshold, the observed breakout geometry;

updating, in response to the comparing and adjusting, mud weight calculations for the drilling operation; and

changing, in real time and in response to the updating, drilling parameters for the drilling operation.

9. The non-transitory, computer-readable medium of claim 8, wherein determining the predicted breakout geometry is based on a pore pressure, a maximum horizontal stress azimuth, a tensile strength, a maximum horizontal stress (σh), a maximum vertical stress (σV), a cohesion friction angle UCS, and a Young Modulus Poisson’s ratio.

10. The non-transitory, computer-readable medium of claim 8, wherein the analytical elastic breakout model uses geomechanical properties from a one-dimensional (1D) Mechanical Earth Model (MEM) and real-time data including an equivalent circulating density (ECD).

11. The non-transitory, computer-readable medium of claim 8, wherein the analytical elastic breakout model supports computing effective stresses in combination with shear failure criteria.

12. The non-transitory, computer-readable medium of claim 11, wherein computing the effective stresses includes computing various elastic solutions and poroelastic solutions.

13. The non-transitory, computer-readable medium of claim 11, wherein the shear failure criteria include Mohr-Coulomb, Drucker-Prager, modified Lade, and Mogi-Coulomb techniques.

14. The non-transitory, computer-readable medium of claim 8, wherein adjusting the maximum horizontal stress value in the analytical elastic breakout model includes incrementally adjusting the predicted breakout depth by 1%.

15. A computer-implemented system, comprising:

one or more processors; and

a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors, the programming instructions instructing the one or more processors to perform operations comprising: determining, using an analytical elastic breakout model, a predicted breakout geometry, including determining a predicted breakout width, a predicted breakout depth, and a predicted breakout angle for a drilling operation of a petrochemical well; comparing the predicted breakout geometry with an observed breakout geometry at an observed breakout angle determined in real time using real-time caliper log data obtained from a multi-finger caliper during the drilling operation; adjusting a maximum horizontal stress value in the analytical elastic breakout model until the predicted breakout geometry matches, within a percentage threshold, the observed breakout geometry; updating, in response to the comparing and adjusting, mud weight calculations for the drilling operation; and changing, in real time and in response to the updating, drilling parameters for the drilling operation.

16. The computer-implemented system of claim 15, wherein determining the predicted breakout geometry is based on a pore pressure, a maximum horizontal stress azimuth, a tensile strength, a maximum horizontal stress (σh), a maximum vertical stress (σV), a cohesion friction angle UCS, and a Young Modulus Poisson’s ratio.

17. The computer-implemented system of claim 15, wherein the analytical elastic breakout model uses geomechanical properties from a one-dimensional (1D) Mechanical Earth Model (MEM) and real-time data including an equivalent circulating density (ECD).

18. The computer-implemented system of claim 15, wherein the analytical elastic breakout model supports computing effective stresses in combination with shear failure criteria.

19. The computer-implemented system of claim 18, wherein computing the effective stresses includes computing various elastic solutions and poroelastic solutions.

20. The computer-implemented system of claim 18, wherein the shear failure criteria include Mohr-Coulomb, Drucker-Prager, modified Lade, and Mogi-Coulomb techniques.