Method for detecting a washout or overpressure event using turbine rotations per minute

Abstract

A method for detecting a washout or overpressure event. The method includes receiving data signals from sensors at a wellsite, wherein the data signals include at least one surface originated measurement such as flowrate and a plurality of downhole originated measurements including turbine RPM. After any transient regions or outliers from the received data signals have been removed, a current downhole measurement signal may be compared with at least one previous downhole measurement signal from the same data signal to determine a predicted baseline. A current downhole measurement signal may be reported as suspicious each time it is detected to be lower than a predetermined threshold relative to the predicted baseline. An alarm may then be provided which indicates a washout or overpressure event when a threshold number of suspicious measurement signals have been detected. A wellsite action may then be performed that is based on the activated alarm.

Description

PATENT Attorney Docket No.: IS23.1607-WOMETHOD FOR DETECTING A WASHOUT OR OVERPRESSURE EVENT USINGTURBINE ROTATIONS PER MINUTECross-Reference to Related Applications

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 736,120, filed on December 19, 2024, which is incorporated by reference.Background

[0002] A drillstring washout refers to a hole or cracks in the drillstring (from drill pipe to bit) caused usually by wear, such as corrosion or tensile stress, or by excess shock and vibration. Such weakness can result in a complete twist-off of the pipe, which may cause non productive time due to fishing of the lost components or in the worst case, abandonment of the well. Generally speaking, washouts become more severe with time. Early detection of drillstring washout can help to prevent catastrophic events like twist-offs.

[0003] What is needed is a method to detect early a washout event using turbine RPM (TRPM) and not conventional (stand pipe pressure) SPP methods. The method should be sensitive and detect the washout even when available alarms have failed. Thus, the method should be able to detect the washout at an early stage so as to avoid losing millions of dollars caused by missed washout events or detection which has come too late.Summary

[0004] In certain embodiments, a method is provided for detecting a washout or overpressure event at a wellsite. The method includes receiving data signals from the wellsite and generating a predicted baseline from the filtered data signals. The method further includes comparing a current downhole measurement signal with the predicted baseline, determining that the current downhole measurement signal is indicative of a washout or overpressure event, and activating an alarm in response to determining that current downhole measurement signal is indicative of the washout or overpressure event.

[0005] In certain embodiments, a computing system is provided. The computing system includes one or more processors and a memory system comprising one or more non-transitory computer- readable media storing instructions that, when executed by at least one of the one or morePATENT Attorney Docket No.: IS23.1607-WO processors, cause the computing system to perform operations. The operations include receiving data signals from the wellsite, filtering the received data signals, and generating a predicted baseline from the filtered data signals. The operations further include comparing a current downhole measurement signal with the predicted baseline, reporting the current downhole measurement signal as a suspicious downhole measurement signal each time it is detected to be outside a predetermined threshold relative to the predicted baseline, determining that the suspicious downhole measurement signal is indicative of a washout or overpressure event, and activating an alarm indicating the washout or overpressure event when a threshold number of suspicious downhole measurement signals are determined to be indicative of the washout or overpressure event.

[0006] In certain embodiments, a non-transitory computer-readable medium is provided storing instructions that, when executed by one or more processors of a computing system, cause the computing system to perform operations. The operations include receiving data signals from the wellsite, filtering the received data signals, and generating a predicted baseline from the filtered data signals. The operations further include comparing a current downhole measurement signal with the predicted baseline, reporting the current downhole measurement signal as a suspicious downhole measurement signal each time it is detected to be outside a predetermined threshold relative to the predicted baseline, determining that the suspicious downhole measurement signal is indicative of a washout or overpressure event, and activating an alarm indicating the washout or overpressure event when a threshold number of suspicious downhole measurement signals are determined to be indicative of the washout or overpressure event.Brief Description of the Drawings

[0007] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present teachings and together with the description, serve to explain the principles of the present teachings. In the figures:

[0008] Figure 1 illustrates an example of a system that includes various management components to manage various aspects of a geologic environment, according to an embodiment.

[0009] Figure 2A illustrates a first graphical representation showing transient regions detected in a surface measurement, according to an embodiment.PATENT Attorney Docket No.: IS23.1607-WO

[0010] Figure 2B illustrates a second graphical representation showing transient regions detected in an alternative surface measurement, according to an embodiment.

[0011] Figure 3 illustrates a graphical representation showing detected downhole measurement outliers, according to an embodiment.

[0012] Figure 4A illustrates a graphical representation showing a relationship between TRPM and flowrate in a wellbore and a predicted baseline value based on previously received signals, according to an embodiment.

[0013] Figure 4B illustrates the graphical representation of Figure 4A after a number of incoming signals have been marked as suspicious, according to an embodiment.

[0014] Figure 4C illustrates the graphical representation of Figure 4B after the signals marked as suspicious have been compared to a standard deviation threshold, according to an embodiment.

[0015] Figure 5 illustrates graphical representations showing several statistical measures used to detect a washout event, according to an embodiment.

[0016] Figure 6 illustrates an example of a washout event being missed by a conventional SPP- based alarm but which is detected by the current workflow even before an experienced human operator, according to an embodiment.

[0017] Figure 7 illustrates a flowchart of a method for detecting a washout event at a wellsite, according to an embodiment.

[0018] Figure 8 illustrates a schematic view of a computing system for performing at least a portion of the method(s) described herein, according to an embodiment.Detailed Description

[0019] Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings and figures. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to one of ordinary skill in the art that the invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the embodiments.

[0020] It will also be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These termsPATENT Attorney Docket No.: IS23.1607-WO are only used to distinguish one element from another. For example, a first object or step could be termed a second object or step, and, similarly, a second object or step could be termed a first object or step, without departing from the scope of the present disclosure. The first object or step, and the second object or step, are both, objects or steps, respectively, but they are not to be considered the same object or step.

[0021] The terminology used in the description herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used in this description and the appended claims, the singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and / or” as used herein refers to and encompasses any possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Further, as used herein, the term “if’ may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context.

[0022] Attention is now directed to processing procedures, methods, techniques, and workflows that are in accordance with some embodiments. Some operations in the processing procedures, methods, techniques, and workflows disclosed herein may be combined and / or the order of some operations may be changed.System Overview

[0023] Figure 1 illustrates an example of a system 100 that includes various management components 110 to manage various aspects of a geologic environment 150 (e.g., an environment that includes a sedimentary basin, a reservoir 151, one or more faults 153-1, one or more geobodies 153-2, etc.). For example, the management components 110 may allow for direct or indirect management of sensing, drilling, injecting, extracting, etc., with respect to the geologic environment 150. In turn, further information about the geologic environment 150 may become available as feedback 160 (e.g., optionally as input to one or more of the management components 110).PATENT Attorney Docket No.: IS23.1607-WO

[0024] In the example of Figure 1, the management components 1 10 include a seismic data component 112, an additional information component 114 (e.g., well / logging data), a processing component 116, a simulation component 120, an attribute component 130, an analysis / visualization component 142 and a workflow component 144. In operation, seismic data and other information provided per the components 112 and 114 may be input to the simulation component 120.

[0025] In an example embodiment, the simulation component 120 may rely on entities 122. Entities 122 may include earth entities or geological objects such as wells, surfaces, bodies, reservoirs, etc. In the system 100, the entities 122 can include virtual representations of actual physical entities that are reconstructed for purposes of simulation. The entities 122 may include entities based on data acquired via sensing, observation, etc. (e.g., the seismic data 112 and other information 114). An entity may be characterized by one or more properties (e.g., a geometrical pillar grid entity of an earth model may be characterized by a porosity property). Such properties may represent one or more measurements (e.g., acquired data), calculations, etc.

[0026] In an example embodiment, the simulation component 120 may operate in conjunction with a software framework such as an object-based framework. In such a framework, entities may include entities based on pre-defined classes to facilitate modeling and simulation. A commercially available example of an object-based framework is the MICROSOFT® .NET® framework (Redmond, Washington), which provides a set of extensible object classes. In the .NET® framework, an object class encapsulates a module of reusable code and associated data structures. Object classes may be used to instantiate object instances for use in by a program, script, etc. For example, borehole classes may define objects for representing boreholes based on well data.

[0027] In the example of Figure 1, the simulation component 120 may process information to conform to one or more attributes specified by the attribute component 130, which may include a library of attributes. Such processing may occur prior to input to the simulation component 120 (e.g., consider the processing component 116). As an example, the simulation component 120 may perform operations on input information based on one or more attributes specified by the attribute component 130. In an example embodiment, the simulation component 120 may construct one or more models of the geologic environment 150, which may be relied on to simulate behavior of the geologic environment 150 (e.g., responsive to one or more acts, whether natural orPATENT Attorney Docket No.: IS23.1607-WO artificial). In the example of Figure 1, the analysis / visualization component 142 may allow for interaction with a model or model-based results (e.g., simulation results, etc.). As an example, output from the simulation component 120 may be input to one or more other workflows, as indicated by a workflow component 144.

[0028] As an example, the simulation component 120 may include one or more features of a simulator such as the ECLIPSE™ reservoir simulator (SLB, Houston Texas), the INTERSECT™ reservoir simulator (SLB, Houston Texas), etc. As an example, a simulation component, a simulator, etc. may include features to implement one or more meshless techniques (e.g., to solve one or more equations, etc.). As an example, a reservoir or reservoirs may be simulated with respect to one or more enhanced recovery techniques (e.g., consider a thermal process such as SAGD, etc ).

[0029] As an example, the simulation component 120 may include one or more features of a simulator such as SYMMETRY™ software (SLB, Houston, Texas). More particularly, SYMMETRY™ may process workflows in a single integrated environment with accurate thermodynamic fluid representation and consistent modeling across multiple disciplines including process, production, and HSE. The simulator integrates steady-state and transient (e.g., dynamic) analyses that can be tailored for each domain. This approach enables users to optimize processes in upstream, midstream, and downstream sectors while maximizing profits and minimizing capital expenditures. It may also help reduce emissions, energy consumption, and waste.

[0030] As an example, the simulation component 120 may include one or more features of a simulator such as PIPESIM™ (SLB, Houston, Texas). More particularly, PIPESIM™ is steadystate multiphase flow simulator that incorporates the three areas of flow modeling: multiphase flow, heat transfer and fluid behavior.

[0031] As an example, the simulation component 120 may include one or more features of a simulator such as OLGA™ (SLB, Houston, Texas). More particularly, OLGA™ is a dynamic multiphase flow simulator that models transient flow (e.g., time-dependent behaviors) to maximize production potential. Transient modeling is a component for feasibility studies and field development design. Dynamic simulation is useful in deep water and is used in both offshore and onshore developments to investigate transient behavior in pipelines and wellbores. Transient simulation with the OLGA™ simulator provides an added dimension to steady-state analysis byPATENT Attorney Docket No.: IS23.1607-WO predicting system dynamics, such as time-varying changes in flow rates, fluid compositions, temperature, solids deposition, and operational changes.

[0032] In an example embodiment, the management components 110 may include features of a commercially available framework such as the PETREL® seismic to simulation software framework (SLB, Houston, Texas). The PETREL® framework provides components that allow for optimization of exploration and development operations. The PETREL® framework includes seismic to simulation software components that may output information for use in increasing reservoir performance, for example, by improving asset team productivity. Through use of such a framework, various professionals (e.g., geophysicists, geologists, and reservoir engineers) may develop collaborative workflows and integrate operations to streamline processes. Such a framework may be considered an application and may be considered a data-driven application (e.g., where data is input for purposes of modeling, simulating, etc.).

[0033] In an example embodiment, various aspects of the management components 110 may include add-ons or plug-ins that operate according to specifications of a framework environment. For example, a commercially available framework environment marketed as the OCEAN® framework environment (SLB, Houston, Texas) allows for integration of add-ons (or plug-ins) into a PETREL® framework workflow. The OCEAN® framework environment leverages .NET® tools (Microsoft Corporation, Redmond, Washington) and offers stable, user-friendly interfaces for efficient development. In an example embodiment, various components may be implemented as add-ons (or plug-ins) that conform to and operate according to specifications of a framework environment (e.g., according to application programming interface (API) specifications, etc.).

[0034] Figure 1 also shows an example of a framework 170 that includes a model simulation layer 180 along with a framework services layer 190, a framework core layer 195 and a modules layer 175. The framework 170 may include the commercially available OCEAN® framework where the model simulation layer 180 is the commercially available PETREL® model-centric software package that hosts OCEAN® framework applications. In an example embodiment, the PETREL® software may be considered a data-driven application. The PETREL® software may include a framework for model building and visualization.

[0035] As an example, a framework may include features for implementing one or more mesh generation techniques. For example, a framework may include an input component for receipt of information from interpretation of seismic data, one or more attributes based at least in part onPATENT Attorney Docket No.: IS23.1607-WO seismic data, log data, image data, etc. Such a framework may include a mesh generation component that processes input information, optionally in conjunction with other information, to generate a mesh.

[0036] In the example of Figure 1, the model simulation layer 180 may provide domain objects 182, act as a data source 184, provide for rendering 186 and provide for various user interfaces 188. Rendering 186 may provide a graphical environment in which applications may display their data while the user interfaces 188 may provide a common look and feel for application user interface components.

[0037] As an example, the domain objects 182 may include entity objects, property objects and optionally other objects. Entity objects may be used to geometrically represent wells, surfaces, bodies, reservoirs, etc., while property objects may be used to provide property values as well as data versions and display parameters. For example, an entity object may represent a well where a property object provides log information as well as version information and display information (e.g., to display the well as part of a model).

[0038] In the example of Figure 1, data may be stored in one or more data sources (or data stores, generally physical data storage devices), which may be at the same or different physical sites and accessible via one or more networks. The model simulation layer 180 may be configured to model projects. As such, a particular project may be stored where stored project information may include inputs, models, results and cases. Thus, upon completion of a modeling session, a user may store a project. At a later time, the project may be accessed and restored using the model simulation layer 180, which may recreate instances of the relevant domain objects.

[0039] In the example of Figure 1, the geologic environment 150 may include layers (e.g., stratification) that include a reservoir 151 and one or more other features such as the fault 153-1, the geobody 153-2, etc. As an example, the geologic environment 150 may be outfitted with any of a variety of sensors, detectors, actuators, etc. For example, equipment 152 may include communication circuitry to receive and to transmit information with respect to one or more networks 155. Such information may include information associated with downhole equipment 154, which may be equipment to acquire information, to assist with resource recovery, etc. Other equipment 156 may be located remote from a well site and include sensing, detecting, emitting or other circuitry. Such equipment may include storage and communication circuitry to store and to communicate data, instructions, etc. As an example, one or more satellites may be provided forPATENT Attorney Docket No.: IS23.1607-WO purposes of communications, data acquisition, etc. For example, Figure 1 shows a satellite in communication with the network 155 that may be configured for communications, noting that the satellite may additionally or instead include circuitry for imagery (e.g., spatial, spectral, temporal, radiometric, etc.).

[0040] Figure 1 also shows the geologic environment 150 as optionally including equipment 157 and 158 associated with a well that includes a substantially horizontal portion that may intersect with one or more fractures 159. For example, consider a well in a shale formation that may include natural fractures, artificial fractures (e.g., hydraulic fractures) or a combination of natural and artificial fractures. As an example, a well may be drilled for a reservoir that is laterally extensive. In such an example, lateral variations in properties, stresses, etc. may exist where an assessment of such variations may assist with planning, operations, etc. to develop a laterally extensive reservoir (e.g., via fracturing, injecting, extracting, etc.). As an example, the equipment 157 and / or 158 may include components, a system, systems, etc. for fracturing, seismic sensing, analysis of seismic data, assessment of one or more fractures, etc.

[0041] As mentioned, the system 100 may be used to perform one or more workflows. A workflow may be a process that includes a number of worksteps. A workstep may operate on data, for example, to create new data, to update existing data, etc. As an example, a may operate on one or more inputs and create one or more results, for example, based on one or more algorithms. As an example, a system may include a workflow editor for creation, editing, executing, etc. of a workflow. In such an example, the workflow editor may provide for selection of one or more predefined worksteps, one or more customized worksteps, etc. As an example, a workflow may be a workflow implementable in the PETREL® software, for example, that operates on seismic data, seismic attribute(s), etc. As an example, a workflow may be a process implementable in the OCEAN® framework. As an example, a workflow may include one or more worksteps that access a module such as a plug-in (e.g., external executable code, etc.).

[0042] A network architecture for drilling operations typically involves a multi-layered setup designed to handle the complexities of rig environments, as shown in Figure 1. The infrastructure may be segmented into distinct network zones, such as an information technology (IT) network, an operational technology (OT) network, and a rig network, to ensure security and manageability.

[0043] The IT network may include centralized support and monitoring systems, such as the Service Provider Central Support Network, which interacts with the rig networks via securePATENT Attorney Docket No.: IS23.1607-WO communication channels. The OT network may operate within a more restrictive environment, managing essential control systems and acquisition networks, including surface and downhole data acquisition devices. Each network segment is further isolated using firewalls and hypervisor technologies, enabling network segmentation and perimeter security.

[0044] The rig network connects critical edge devices, such as drilling control units, acquisition systems, and other wellsite equipment which perform various automation and data processing tasks. These edge devices often operate with limited bandwidth, making it challenging to transmit large amounts of data in real time. Therefore, a robust strategy for monitoring and data collection is preferred to ensure efficient operation without overwhelming the network.Method for Detecting a Washout or Overpressure Event Using Turbine Rotations Per Minute

[0045] According to certain embodiments, turbines that are disposed in a bottom hole assembly (BHA) may be used to detect potential washout or overpressure. If a washout occurs above the BHA, the mud flow to the turbine may be reduced compared to the surface measurements. If the flowrate is kept constant at the surface, but there is a drop in turbine's rotations per minute (TRPM) detected downhole, it might be an indicator for a washout, according to an embodiment, since TRPM is directly proportional to the flowrate. Thus, TRPM may be used to detect washout. According to certain embodiments, the workflow of the present disclosure may use at least two signals: flowrate and TRPM. The workflow may be based on numerous statistical measures computed in real time and is able to reliably detect a washout event even when conventional alarms based on stand pipe pressure (SPP) methods have failed.

[0046] According to certain embodiments, the workflow of the present disclosure functions in real time by first accumulating data points from the wellsite until there is enough to perform further analysis. Next, a surface measurements signal, such as flowrate, may be analyzed to detect transient regions. Figures 2A-2B illustrate examples 200, 210 of transient regions 202 being detected within a flowrate over time. Transient regions 202 may be created when the wellsite is in flux, for example, when the concentration of the fluid flow within the wellbore is being adjusted or when the trajectory of the drillstring is being redirected. The current workflow may also capture downlinking, according to an embodiment.

[0047] In certain embodiments, these transient regions 202 may be excluded from the further statistical analysis as they are “unreliable” because of a highly fluctuating flowrate. Figure 3PATENT Attorney Docket No.: IS23.1607-WO shows a graphical representation 300 illustrating an example of detected TRPM outliers 302 and a plurality of transient points 304 detected at respective flowrate points. Additionally, corresponding points from other data channels may be also excluded.

[0048] According to certain embodiments, downhole measurement signals such as TRPM or collar rotation per minute (CRPM) may be analyzed in order detect and exclude outlier data. Outlier data may occur due to failing signal processing or sensors. For example, incoming data may provide extremely large or extremely small values which if not excluded would negatively impact the workflow. Additionally, corresponding points from other channels may also be excluded.

[0049] According to certain embodiments and as seen in Figure 4A, with a “clean” flowrate and TRPM signal, the workflow may include performing a one dimensional polynomial fit 402 using the data points that have thus far been accumulated using Equation 1 :TRPM = a*Flowrate + b (1)

[0050] According to certain embodiments, when using an application with a mud motor above a rotary steerable system (RSS), with a “clean” flowrate and CRPM signal from RSS, the workflow may include performing a one dimensional polynomial fit using the data points that have thus far been accumulated using Equation 1 :CRPM = a*Flowrate + b (2)

[0051] In certain embodiments, the quality of these fits in equation (1) or equation (2) may be evaluated along with the uncertainty of the linear regression fit and numerous other statistical parameters. These values may then be stored in a memory of the system. For example, as current TRPM values 404 are received, they may then be compared with those that would have been obtained if an earlier fit coefficient would have been used represented by a band 406 which surrounds the polynomial fit 402 as illustrated in Figure 4B. For instance, TRPM values are predicted using the earlier accumulated polynomial fit coefficients and may be compared to the current TRPM values 404 to determine a specific likelihood that a washout event is occurring. In certain embodiments, if after an initial comparison it is likely that a washout event has been detected, a second comparison may be performed. Here, additional earlier points may be used from the preceding signal to compute a joint washout probability. This newly developed measure takes into account washout probability at the current point and several preceding points to determine anPATENT Attorney Docket No.: IS23.1607-WO even more specific or detailed likelihood that a washout event is occurring. If this joint washout probability exceeds a given threshold, this data point may be reported as a suspicious point 408 as seen in Figure 4B. In certain embodiments, if the fit quality is determined to be significantly worse, this data point may be reported again. For example, the actual error, which in certain embodiments may be the orthogonal distance between the suspicious point 408 to a projection on the polynomial fit 402, may be calculated and then compared to a predetermined standard deviation of fit 410. If the suspicious point 408 is beyond the predetermined standard deviation of fit 410, the suspicious point 408 may be reported out again as a potential washout point 412 to the drilling professional as seen in Figure 4C. This procedure may be repeated until a certain predetermined number of data points have been reported as suspicious and certain statistical criteria have been met. In certain embodiments, if the required statistical criteria have been met, a washout event may be reported. In certain embodiments, because the current workflow uses at least two signals in order to detect a potential washout event in real time, namely TRPM and flowrate, no prior assumptions related to BHA are needed.

[0052] In certain embodiments, the predetermined standard deviation of fit 410 may be varied or customized based on geographic conditions. For example, the standard deviation of fit 410 may be based on the expected geographic features beneath the planned wellbore, thereby providing a standard deviation of fit 410 that may be location specific or even unique to one wellbore or set of wellbores.

[0053] For all such suspicious points, numerous further statistics, for example those included in Figure 5 which may include, but are not limited to F statistics, a coefficient of determination (R2score) of the liner model illustrating TRPM as a function of flowrate, a mean average percentage error (MAPE) of the TRPM value prediction, and a covariance between flowrate and TRPM, may be calculated then used to compare the current fit quality to previously received values. In certain embodiments, any statistic which describes or detects the relationship between TRPM and flowrate may be calculated and used to determine the occurrence of a washout or overpressure event.

[0054] In summary and according to certain embodiments, a turbine that may be a part of the bottom hole assembly may be used to detect a washout event. Figure 6 illustrates an example of a washout event being missed by a conventional SPP-based alarm, but which is detected by the current workflow even before an experienced human operator. In certain embodiments, sensors disposed on the bottom hole assembly send the TRPM values that can be used for a washout eventPATENT Attorney Docket No.: IS23.1607-WO alarm. Being able to detect a washout in a timely manner is critical as it would not only avoid the potential loss of millions of dollars but would also help mitigate any related safety issues.

[0055] An advantage of the current workflow is that no prior information is required about the turbine and the BHA. Frequently, people may use this meta data and base their methods on the comparison of what is expected based on the BHA to what is observed. The current workflow is independent of the meta information and is thus more widely applicable as the BHA is not always communicated between different services. Additionally, using TRPM is a more sensitive indicator of a washout event as compared to monitoring the SPP. In certain embodiments, by only using TRPM and flowrate to detect a washout event, no additional signals are needed which in turn leads to less dependencies on other sensors, equipment, etc.Exemplary Method

[0056] Figure 7 illustrates a flowchart of a method 700 for detecting a washout or overpressure event at a wellsite. An illustrative order of the method 700 is provided below; however, one or more portions of the method 700 may be performed in a different order, simultaneously, repeated, or omitted. At least a portion of the method 700 may be performed using a computing system.

[0057] In certain embodiments, the method 700 includes receiving data signals from the wellsite as at 702. The data signals may include at least one surface originated measurement from the wellsite and a plurality of downhole originated measurements from the wellsite. The surface originated measurement from the wellsite may include a flowrate signal or at least one flowrate signal in combination with a standpipe pressure (SPP) signal, differential pressure signals, and / or a weight on bit (WOB) signal. The downhole measurements may include, for example, at least one turbine RPM (TRPM) signal or a TRPM signal in combination with downhole internal pressure signals, downhole external pressure signals, and / or downhole flow signals.

[0058] According to certain embodiments, the method 700 may also include filtering the received data signals as at 704. Filtering the received data signals may include detecting and removing any transient regions from the received data signals. Filtering the received data signals may include detecting and removing any outliers from the received data signals.

[0059] According to certain embodiments, the method 700 may also include generating a predicted baseline from the filtered data signals as at 706. The predicted baseline may be generatedPATENT Attorney Docket No.: IS23.1607-WO by performing a one dimensional polynomial fit using data points that have thus far been accumulated.

[0060] According to certain embodiments, the method 700 may also include comparing a current downhole measurement signal with the predicted baseline as at 708. Comparing the current downhole measurement signal with the predicted baseline may include determining if the current downhole measurement signal is within a band of values defined around the predicted baseline. In certain embodiments, reporting the current downhole measurement signal as a suspicious downhole measurement signal each time it is detected to be outside the predetermined threshold relative to the predicted baseline may include reporting the current downhole measurement signal as suspicious when it is determined to be outside of the band of values defined around the predicted baseline. Comparing the current downhole measurement signal with the predicted baseline may include comparing the current downhole measurement signal to a first set of previous downhole measurement values to provide a first confidence index indicative of a washout or overpressure event.

[0061] According to certain embodiments, the method 700 may also include reporting the current downhole measurement signal as a suspicious downhole measurement signal each time it is detected to be outside a predetermined threshold relative to the predicted baseline as at 710.

[0062] According to certain embodiments, the method 700 may also include determining if the suspicious downhole measurement signal is indicative of a washout or overpressure event as at 712. Determining if the suspicious downhole measurement signal is indicative of the washout or overpressure event may include determining if the suspicious downhole measurement is lower than a predetermined standard deviation relative to the predicted baseline or higher than the predetermined standard deviation relative to the predicted baseline, respectively. The predetermined standard deviation relative to the predicted baseline may be based on a plurality of geographic conditions at the wellsite. In certain embodiments, determining if the suspicious downhole measurement signal is indicative of the washout or overpressure event may include comparing the suspicious downhole measurement signal to a second set of previous downhole measurement values to provide a second confidence index when the first confidence index is indicative of the washout or overpressure event. The second set of previous downhole measurement signals may include more downhole measurement signals relative to the first set of previous downhole measurement signals. In certain embodiments, determining if the suspiciousPATENT Attorney Docket No.: IS23.1607-WO downhole measurement signal is indicative of the washout or overpressure event includes determining an actual error between the suspicious downhole measurement signal and the predicted baseline and comparing the actual error to a predetermined standard deviation relative to the predicted baseline.

[0063] According to certain embodiments, the method 700 may also include activating an alarm indicating the washout or overpressure event when a threshold number of suspicious downhole measurement signals are determined to be indicative of the washout or overpressure event as at 714. Activating the alarm may include sending an alarm indicator which includes a determined probability of the washout or overpressure event and the second confidence index when indicative of the washout or overpressure event.

[0064] According to certain embodiments, the method 700 may also include updating the predicted baseline based on at least one newly received data signal from the wellsite as at 716.

[0065] According to certain embodiments, the method 700 may also include performing a wellsite action based on the activated alarm as at 718. Performing the wellsite action may include generating or transmitting a signal that instructs or causes an action to occur. The action may include a physical action. The physical action my include selecting where to drill a wellbore in the subsurface formation, drilling the wellbore, varying a trajectory of the wellbore, varying a weight or torque on a drill bit that is drilling the wellbore, varying a rate or concentration of a fluid being pumped into the wellbore, deciding to stop drilling and pull the downhole equipment up before causing a twist-off, reviewing the wellbore, cleaning the wellbore, slowing a rate of the drill, or a combination thereof. The wellsite action may be based on a determined confidence index.Exemplary Computing System

[0066] In some embodiments, the methods of the present disclosure may be executed by a computing system. Figure 8 illustrates an example of such a computing system 800, in accordance with some embodiments. The computing system 800 may include a computer or computer system 801A, which may be an individual computer system 801A or an arrangement of distributed computer systems. The computer system 801 A includes one or more analysis modules 802 that are configured to perform various tasks according to some embodiments, such as one or more methods disclosed herein. To perform these various tasks, the analysis module 802 executes independently, or in coordination with, one or more processors 804, which is (or are) connected toPATENT Attorney Docket No.: IS23.1607-WO one or more storage media 806. The processor(s) 804 is (or are) also connected to a network interface 807 to allow the computer system 801 A to communicate over a data network 809 with one or more additional computer systems and / or computing systems, such as 80 IB, 801C, and / or 801D (note that computer systems 801B, 801C and / or 801D may or may not share the same architecture as computer system 801 A, and may be located in different physical locations, e.g., computer systems 801A and 801B may be located in a processing facility, while in communication with one or more computer systems such as 801 C and / or 80 ID that are located in one or more data centers, and / or located in varying countries on different continents).

[0067] A processor may include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.

[0068] The storage media 806 may be implemented as one or more computer-readable or machine-readable storage media. Note that while in the example embodiment of Figure 8 storage media 806 is depicted as within computer system 801 A, in some embodiments, storage media 806 may be distributed within and / or across multiple internal and / or external enclosures of computing system 801A and / or additional computing systems. Storage media 806 may include one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories, magnetic disks such as fixed, floppy and removable disks, other magnetic media including tape, optical media such as compact disks (CDs) or digital video disks (DVDs), B LURAY® disks, or other types of optical storage, or other types of storage devices. Note that the instructions discussed above may be provided on one computer-readable or machine-readable storage medium, or may be provided on multiple computer-readable or machine-readable storage media distributed in a large system having possibly plural nodes. Such computer-readable or machine-readable storage medium or media is (are) considered to be part of an article (or article of manufacture). An article or article of manufacture may refer to any manufactured single component or multiple components. The storage medium or media may be located either in the machine running the machine-readable instructions, or located at a remote site from which machine-readable instructions may be downloaded over a network for execution.PATENT Attorney Docket No.: IS23.1607-WO

[0069] It should be appreciated that computing system 800 is merely one example of a computing system, and that computing system 800 may have more or fewer components than shown, may combine additional components not depicted in the example embodiment of Figure 8, and / or computing system 800 may have a different configuration or arrangement of the components depicted in Figure 8. The various components shown in Figure 8 may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and / or application specific integrated circuits.

[0070] Further, the steps in the processing methods described herein may be implemented by running one or more functional modules in information processing apparatus such as general purpose processors or application specific chips, such as ASICs, FPGAs, PLDs, or other appropriate devices. These modules, combinations of these modules, and / or their combination with general hardware are included within the scope of the present disclosure.

[0071] Computational interpretations, models, and / or other interpretation aids may be refined in an iterative fashion; this concept is applicable to the methods discussed herein. This may include use of feedback loops executed on an algorithmic basis, such as at a computing device (e.g., computing system 800, Figure 8), and / or through manual control by a user who may make determinations regarding whether a given step, action, template, model, or set of curves has become sufficiently accurate for the evaluation of the risk index.

[0072] The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or limiting to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. Moreover, the order in which the elements of the methods described herein are illustrated and described may be re-arranged, and / or two or more elements may occur simultaneously. The embodiments were chosen and described in order to best explain the principles of the disclosure and its practical applications, to thereby enable others skilled in the art to best utilize the disclosed embodiments and various embodiments with various modifications as are suited to the particular use contemplated.

Claims

PATENT Attorney Docket No.: IS23.1607-WOCLAIMSWhat is claimed is:

1. A method for detecting a washout or overpressure event at a wellsite, the method comprising: receiving data signals from the wellsite; generating a predicted baseline from the data signals; comparing a current downhole measurement signal with the predicted baseline; determining that the current downhole measurement signal is indicative of a washout or overpressure event in response to the comparison; and activating an alarm in response to determining that the current downhole measurement signal is indicative of the washout or overpressure event.

2. The method of claim 1, further comprising reporting the current downhole measurement signal as a suspicious downhole measurement signal each time it is detected to be outside a predetermined threshold relative to the predicted baseline, wherein determining that the suspicious downhole measurement signal is indicative of the washout or overpressure event comprises determining that the suspicious downhole measurement is lower than a predetermined standard deviation relative to the predicted baseline or higher than the predetermined standard deviation relative to the predicted baseline, respectively.

3. The method of claim 2, wherein the predetermined standard deviation relative to the predicted baseline is based on a plurality of geographic conditions at the wellsite.

4. The method of claim 1, wherein the received data signals comprise at least one surface originated measurement from the wellsite and a plurality of downhole originated measurements from the wellsite.

5. The method of claim 4, wherein the surface originated measurement from the wellsite comprises a flowrate signal or at least one flowrate signal in combination with a standpipe pressure (SPP) signal, differential pressure signals, and / or a weight on bit (WOB) signal.PATENT Attorney Docket No.: IS23.1607-WO6. The method of claim 4, wherein the downhole originated measurements comprise: at least one turbine RPM (TRPM) signal; or a TRPM signal in combination with a plurality of downhole internal pressure signals, downhole external pressure signals, and / or downhole flow signals.

7. The method of claim 1, wherein filtering the received data signals comprises detecting and removing any transient regions from the received data signals.

8. The method of claim 1, wherein filtering the received data signals comprises detecting and removing any outliers from the received data signals.

9. The method of claim 1, wherein comparing the current downhole measurement signal with the predicted baseline comprises determining that the current downhole measurement signal is within a band of values defined around the predicted baseline.

10. The method of claim 9, wherein the received data signals do not comprise a standpipe pressure (SPP) signal.

11. A computing system, comprising: one or more processors; and a memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations comprising: receiving data signals from sensors disposed at the wellsite; filtering the received data signals; generating a predicted baseline from the filtered data signals; comparing a current downhole measurement signal with the predicted baseline; reporting the current downhole measurement signal as a suspicious downhole measurement signal each time it is detected to be outside a predetermined threshold relative to the predicted baseline;PATENT Attorney Docket No.: IS23.1607-WO determining that the suspicious downhole measurement signal is indicative of a washout or overpressure event; and activating an alarm indicating the washout or overpressure event when a threshold number of suspicious downhole measurement signals are determined to be indicative of the washout or overpressure event.

12. The computing system of claim 11, wherein comparing the current downhole measurement signal with the predicted baseline comprises comparing the current downhole measurement signal to a first set of previous downhole measurement values to provide a first confidence index indicative of a washout or overpressure event.

13. The computing system of claim 12, wherein determining that the suspicious downhole measurement signal is indicative of the washout or overpressure event comprises comparing the suspicious downhole measurement signal to a second set of previous downhole measurement values to provide a second confidence index when the first confidence index is indicative of the washout or overpressure event.

14. The computing system of claim 13, wherein the second set of previous downhole measurement signals comprises more downhole measurement signals relative to the first set of previous downhole measurement signals.

15. The computing system of claim 11, wherein determining that the suspicious downhole measurement signal is indicative of the washout or overpressure event comprises: determining an actual error between the suspicious downhole measurement signal and the predicted baseline; and comparing the actual error to a predetermined standard deviation relative to the predicted baseline.

16. The computing system of claim 11, wherein the operations further comprise updating the predicted baseline based on at least one newly received data signal from the wellsite.PATENT Attorney Docket No.: IS23.1607-WO17. The computing system of claim 13, wherein activating the alarm comprises sending an alarm indicator comprising a determined probability of the washout or overpressure event and the second confidence index when indicative of the washout or overpressure event.

18. The computing system of claim 11, wherein the operations further comprise performing a wellsite action based on the activated alarm, wherein performing the wellsite action comprises generating or transmitting a signal that instructs or causes an action to occur, wherein the action comprises a physical action, and wherein the physical action comprises varying a weight or torque on a drill bit that is drilling the wellbore, varying a rate or concentration of a fluid being pumped into the wellbore, deciding to stop drilling and pull downhole equipment up before causing a twist- off, reviewing the wellbore, cleaning the wellbore, slowing a rate of the drill, or a combination thereof.

19. The computing system of claim 18, wherein the wellsite action is based on a determined confidence index.

20. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing system, cause the computing system to perform operations, the operations comprising: receiving data signals from sensors disposed at the wellsite; filtering the received data signals; generating a predicted baseline from the filtered data signals; comparing a current downhole measurement signal with the predicted baseline; reporting the current downhole measurement signal as a suspicious downhole measurement signal each time it is detected to be outside a predetermined threshold relative to the predicted baseline; determining that the suspicious downhole measurement signal is indicative of a washout or overpressure event; and activating an alarm indicating the washout or overpressure event when a threshold number of suspicious downhole measurement signals are determined to be indicative of the washout or overpressure event.

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