Digital well operation diagnostic

Abstract

A method for determining a performance of a well with an electrical submersible pump (ESP) therein includes receiving input data related to the well. The method also includes generating an ESP curve based upon the input data. The method also includes generating a nodal analysis plot based upon the input data. The method also includes determining a mechanical status of the well based upon the input data. The method also includes determining the performance of the well based upon the ESP curve, the nodal analysis plot, and the mechanical status of the well.

Description

Attorney Docket No.: IS24.1111-WO-PCTDIGITAL WELL OPERATION DIAGNOSTICCross-Reference to Related Applications

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 692,785, filed on September 10, 2024, which is incorporated by reference herein.Background

[0002] A technical team overseeing oil production operations from one or more wells employs digital solutions to collect a wide range of operational data, both high-frequency and sporadic. Examples of this data may include pump inlet pressure, pump discharge pressure, current consumption, pump frequency, as well as wellhead pressures and temperatures. While this comprehensive dataset facilitates a detailed understanding of well responses during specific operational events, the analysis conducted by individuals is subject to non-objective factors such as varying technical experience, time constraints, and even human conditions, which may impact the effectiveness of a manual analysis.

[0003] Therefore, what is needed is an improved system and method for performing digital well operation diagnostics.Summary

[0004] A method for determining a performance of a well with an electrical submersible pump (ESP) therein is disclosed. The method includes receiving input data related to the well. The method also includes generating an ESP curve based upon the input data. The method also includes generating a nodal analysis plot based upon the input data. The method also includes determining a mechanical status of the well based upon the input data. The method also includes determining the performance of the well based upon the ESP curve, the nodal analysis plot, and the mechanical status of the well.

[0005] A computing system is also disclosed. The computing system includes one or more processors and a memory system. The memory system includes 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 include receiving input data related to the well. The well has an electrical submersible pump (ESP) therein.Attorney Docket No.: IS24.1111-WO-PCTThe operations also include generating an ESP curve based upon the input data. The operations also include generating a nodal analysis plot based upon the input data. The operations also include determining a mechanical status of the well based upon the input data. The operations also include determining the performance of the well based upon the ESP curve, the nodal analysis plot, and the mechanical status of the well.

[0006] A non-transitory computer-readable medium is also disclosed. The medium stores instructions that, when executed by one or more processors of a computing system, cause the computing system to perform operations. The operations include receiving input data related to the well. The well has an electrical submersible pump (ESP) therein. The operations also include generating an ESP curve based upon the input data. The operations also include generating a nodal analysis plot based upon the input data. The operations also include determining a mechanical status of the well based upon the input data. The operations also include determining the performance of the well based upon the ESP curve, the nodal analysis plot, and the mechanical status of the well.

[0007] It will be appreciated that this summary is intended merely to introduce some aspects of the present methods, systems, and media, which are more fully described and / or claimed below. Accordingly, this summary is not intended to be limiting.Brief Description of the Drawings

[0008] 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:

[0009] 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.

[0010] Figure 2 illustrates an ESP curve, according to an embodiment.

[0011] Figure 3 illustrates a nodal analysis plot, according to an embodiment.

[0012] Figure 4 illustrates a well schematic that provides details about the size and length of various components, along with their respective depths, according to an embodiment.

[0013] Figure 5 illustrates a matrix of operational conditions and their combinations for identifying specific events, according to an embodiment.

[0014] Figure 6 illustrates a WOD algorithm, according to an embodiment.Attorney Docket No.: IS24.1111-WO-PCT

[0015] Figure 7 illustrates a table showing current consumption and WHT, according to an embodiment.

[0016] Figure 8 illustrates a graph showing current consumption versus pump boots effect, according to an embodiment.

[0017] Figure 9 illustrates a hydraulic simulator screen that may be used to generate sensitivities, according to an embodiment.

[0018] Figure 10 illustrates a flowchart of a method for diagnosing a well operation, according to an embodiment.

[0019] Figure 11 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

[0020] 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 present disclosure. However, it will be apparent to one of ordinary skill in the art that the present disclosure 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.

[0021] 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 terms 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.

[0022] 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 associatedAttorney Docket No.: IS24.1111-WO-PCT 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.

[0023] 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

[0024] 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).

[0025] In the example of Figure 1, the management components 110 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.

[0026] 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 may 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 otherAttorney Docket No.: IS24.1111-WO-PCT 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.

[0027] 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.

[0028] 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 or 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.

[0029] 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 ).Attorney Docket No.: IS24.1111-WO-PCT

[0030] 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.).

[0031] 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.).

[0032] 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.

[0033] 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 on seismic data, log data, image data, etc. Such a framework may include a mesh generationAttorney Docket No.: IS24.1111-WO-PCT component that processes input information, optionally in conjunction with other information, to generate a mesh.

[0034] 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.

[0035] 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).

[0036] 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.

[0037] 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 for purposes of communications, data acquisition, etc. For example, Figure 1 shows a satellite inAttorney Docket No.: IS24.1111-WO-PCT 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.).

[0038] 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.

[0039] 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.).Digital Well Operation Diagnostic

[0040] The present disclosure includes an ESP well operation diagnostic (WOD) tool designed for electric submersible pump (ESP) wells. The method described herein utilizes the operational conditions (e.g., instrumentalized system sensors data) of an ESP well to interpret events and assess the performance of the well -reservoir system. The WOD tool uses a calibrated well model, vertical lift performance (VLP), and inflow performance relationship (IPR) models that representAttorney Docket No.: IS24.1111-WO-PCT the reservoir deliverability to a wellbore, to gather insights into three aspects of the production system: (1) the ESP curve performance (e.g., including head, power, and efficiency versus production rate), (2) the mechanical status of the well, and (3) its nodal analysis plot. Subsequently, the WOD scans the behavior and tendencies of the operational conditions, interprets the performance of the system, and identifies potential abnormalities and production optimization opportunities.

[0041] The results may be presented in a visual advisory / alarm format. The solution provides insights into three aspects of the production system. Firstly, it focuses on the ESP, estimating its efficiency and evaluating potential effects of gas production and mechanical degradation, including erosion, internal blockage, or a broken shaft. Secondly, it examines the relationship between the reservoir and the wellbore, utilizing pressure data to identify changes in skin factor and consequences of reservoir pressure variations (e g., a waterflooding effect). Thirdly, it assesses the behavior of the tubing and wellhead, searching for alterations in the produced fluid density, and new surface flowline interconnections that may impact well head pressure (e.g., backpressure).

[0042] The uniqueness of the WOD tool lies in its ability to present a tailored evaluation of the production system, adjusting to the specific conditions of each well by considering both its reservoir behavior (e.g., deliverability) and completion performance (e.g., ESP, tubing and surface equipment). The WOD may support any technical or surveillance team by identifying deviations from the expected conditions of a well -reservoir system. Its diagnostic capabilities are autonomous without human interaction, and consequently the tool may be a surveillance assistant providing insights that reveal what events and wells to focus on.

[0043] The WOD assistance leverages the capability and resources of a control or surveillance center, expanding from numerical set alarms to automatic and immediate diagnostics. This smart monitoring system may be seamlessly integrated into an existing database and deployed visualization, enhancing its technical capabilities with minimal interference during development.Electrical Submersible Pump Curve

[0044] Figure 2 illustrates an ESP curve, according to an embodiment. The ESP curve describes the performance of a specific pump. It illustrates the discharge head developed by the pump, the brake horsepower (e.g., power consumption curve), and the efficiency of the pump as a functionAttorney Docket No.: IS24.1111-WO-PCT of flow rate. This curve is experimental and provided by the manufacturer. It is obtained with freshwater at 60 °F (S.G. = 1) under controlled conditions. The curve may be available for 60 Hz operation and designed to represent the performance of one or more stages of each pump curve. The curve provides the performance of the head, power, and efficiency as a function of the production rate. Hence, it enables an understanding of the expected behavior of these parameters for specific production rate ranges, which in some cases, may be counterintuitive.Nodal Analysis Plot

[0045] Figure 3 illustrates a nodal analysis plot, according to an embodiment. For the WOD workflow, the analysis nodal plot may not incorporate the ESP. Thus, it represents the calibrated vertical lift performance curve (VLP) and the inflow performance relationship (IPR). The VLP curve may be interpreted as the energy values (e.g., as a function of flow rate) to lift the desired production volume from the bottom-hole against a specific WHP. The VLP depends on the well head pressure and three distinct pressure drops:• Hydrostatic pressure drop: defined by the density of the fluid, it represents the weight of the fluid column.• Friction pressure drop: Influenced by the flow regime, viscosity of the fluid, production rate, and diameter of the tubing.• Kinetic pressure drop: it is a function of the velocity changes of the fluid. However, in oil wells where the tubing size remains constant assuming no deposits nor restrictions, this factor, kinetic drop pressure, is considered negligible.

[0046] It is possible to use the nodal analysis curve to identify an approximation of the friction pressure drop and changes in the slope of the VLP curve as a function of the production rate (e.g., as shown in Figure 3). A negative VLP slope occurs at low production rates because the gas phase may flow faster than the liquid phase, generating a heavier column. This phenomenon is known as liquid slippage, and it increases the liquid hold-up. After a certain production rate, this effect disappears, and the VLP slope turns positive. It is then dominated by the increase in friction pressure drop as production increases at constant GOR, WHP and SG.Mechanical Well Status (well diagram schematic)Attorney Docket No.: IS24.1111-WO-PCT

[0047] Figure 4 illustrates a well schematic that provides details about the size and length of various components, along with their respective depths, according to an embodiment. This diagram offers information about the location of operational sensors, providing insights into the expected behavior of their readings and aiding in their tendency interpretation. For instance, the distance between the pump intake pressure (PIP) sensor and the average mid perforation is helpful in defining its PIP response to water cut changes. If the distance is small, an increase in water cut may lead to an increase in PIP at a constant frequency. However, if the distance is large, an increase in water cut may result in a decrease in PIP. This effect is attributed to a combination of two water characteristics: the high mobility of water, which reduces the pressure drop between the reservoir and the wellbore, and the density of the water, which increases the hydrostatic pressure drop.

[0048] Figure 5 illustrates a table including a matrix of operational conditions and their combinations for identifying specific events, according to an embodiment. Some of them are from troubleshooting and are enhanced / improved by adding the WOD approach.

[0049] Another example is the size of the tubing, which defines the liquid hold-up effect and its influences in the vertical lift performance (VLP) behavior. The ESP pump curve (Figure 2), the nodal analysis (Figure 3), and the well diagram (Figure 4) may be used to populate a table (Figure 5) that is specific for each well and its production range. The table in Figure 5 is the base to develop the well operation diagnostic.Proposed solution

[0050] The WOD tool may analyze the short-term history data set to establish trends of the most relevant ESP parameters. They may be set as pump intake pressure (PIP), pump outlet pressure (POP), wellhead pressure (WHP), wellhead temperature (WHT), pump frequency (Hz), and current consumption (Amp), among others. The tendencies result from the interaction of three system components: the VLP curve (excluding the pump), the ESP pump curve, and the IPR curve. The intersection of the VLP and ESP pump curves produces a sequence corresponding to the pump outlet pressure (POP). Similarly, the intersection of the IPR and ESP pump curves generates a sequence corresponding to the pump inlet pressure values (PIP). These PIP and POP values are helpful for interpreting the behavior of the well -reservoir system.Attorney Docket No.: IS24.1111-WO-PCT

[0051] Figure 6 illustrates a WOD algorithm, according to an embodiment. One parameter for evaluating the system is the boots effect of the ESP pump, defined as the difference between the pump outlet pressure and the pump inlet pressure. The WOD tool utilizes the tendency of the delta pressure in the pump to initiate the identification of events and diagnose their potential sources.

[0052] Figure 7 illustrates a table showing current consumption and WHT, according to an embodiment. In one embodiment, the power consumption and the wellhead temperature (WHT) may be used to confirm the trend direction of the liquid production rate. For instance, an increase in WHT or power consumption suggests an increase in production rate, while a decrease in WHT or power consumption suggests a decrease in production rate (Figure 7) at a constant fluid density.

[0053] In another embodiment, the power consumption may fail to confirm this trend under certain scenarios (e.g., emulsions). Consequently, an equation (see Equation 6 below) has been developed that is based on a heat balance at the bottom hole of the well, which incorporates the temperature of the ESP motor and the temperature reported by the pump sensors to confirm the trend direction of the liquid production rate. Therefore, it may no longer be assumed that there is a direct relationship between power consumption and the magnitude of the production rate.Consistency of the pump boots effect compared to the current consumption

[0054] Figure 8 illustrates a graph showing current consumption versus pump boots effect, according to an embodiment. Usually, there is a direct relation between the power consumption and the pump boots effect. Thus, it is possible to establish a linear correlation under stable conditions such as a constant frequency. However, sometimes, there are deviations from the linear behavior. For instance, at the same production rate, if the fluid density increases, the pump boots effect is going to increase without much impact on the power consumption. In another embodiment, if the solids production increases, the power consumption is going to increase without much impact in the pump boots effect. This relationship may be used as a reference to identify changes in the production system (Figure 8).Continuous improvement module

[0055] Figure 9 illustrates a hydraulic simulator screen that may be used to generate sensitivities, according to an embodiment. A well operation diagnostic tool is a live application that uses field data to interpret the performance of a well-reservoir system when the ESP isAttorney Docket No.: IS24.1111-WO-PCT deployed, and there is a set of downhole sensors and a VSD at the surface. The learning curve may be slow and sometimes undesirable in terms of production losses. The method described herein establishes a module of continuous improvement based on well simulation model using software (e.g., PIPESIM® and / or DesignPro®).

[0056] One objective of the continuous improvement module is to select a set of wells that includes a wide range of operational conditions, such as wells with high / low GOR, high / low water cut, unstable water cut, high / low production rate, solid production, waterflooding effect, etc. The module then simulates multiple scenarios, varying factors such as water cut (e.g., density and viscosity of the fluid) and collects input and output data. For example, simulating a well with changing water cut and collecting the responses in operational parameters (Figure 9).

[0057] The outcomes of this process may be integrated into the WOD algorithm, enhancing its performance, and expediting the development process without introducing any risk to real well operations. Furthermore, the utilization of a hydraulic simulator may lead to the identification of additional scenarios and their corresponding operational “fingerprints.”Conclusions

[0058] The method described herein lays the groundwork for the development of a digital application. This present disclosure elucidates how the WOD adheres to production engineering principles to comprehend the behavior of the well, reservoir, and artificial lift system.

[0059] Several comments and expectations regarding this discussion include:1. The establishment of a well validation procedure is helpful to ensure the quality of the data reference for calibration purposes and error calculation.2. The new method adheres to the foundation of production engineering, ensuring alignment with the physics of oil well production.3. WOD may provide a continuous 24 / 7 monitoring solution for the oil producer well operation.4. The future application of this solution may be combined with Artificial Intelligence methods to enhance the accuracy of the prediction and diagnostic.

[0060] One application is the flowrate estimation of production for ESP wells under changing operational conditions and efficiency (e.g., mechanical and / or volumetric). The WOD tool applies to oil wells with high / low GOR, high / low water cut, and water producer wells. The aggregationAttorney Docket No.: IS24.1111-WO-PCT of flow rates and volumes may facilitate volume balance of pads, stations, and fields. The WOD tool supports any technical or surveillance team by identifying deviations from the expected conditions of a well -reservoir system. Its diagnostic capabilities are autonomous without human interaction, and consequently, the tool may provide surveillance assistance insights that reveal what events and wells to focus on. The WOD assistant leverages the capability and resources of control or surveillance center, expanding from numerical set alarms to automatic and immediate diagnostics. This smart monitoring system may be seamlessly integrated into an existing database and deployed visualization, enhancing its technical capabilities with minimal interference during development. In addition, it allows the early detection of conditions that may affect the integrity of the well operation and its production, due to the almost real time diagnostics. Thus, production losses may be minimized, and the life of the well system may be extended with the consequential cost reduction.Using Thermal Balance to Estimate Fluid Flow in ESP Systems

[0061] Electrical submersible pump (ESP) systems are widely used in artificial lift applications to enhance hydrocarbon production. Understanding the thermal behavior of ESP components provides valuable insight into system efficiency and production trends. This following introduces a simplified thermal balance approach for estimating relative changes in fluid flow rates, leveraging temperature and electrical data commonly measured in downhole operations.

[0062] The foundation of this method lies in the characteristic behavior of induction motors. It is well-documented that such motors reach peak efficiency at approximately 75% of their rated load. Efficiency remains relatively stable between 50% and 100% of the rated load but declines below this operating range.

[0063] A motor’s heat dissipation is proportional to the power loss, which is the difference between the electrical input power and the useful output power:Q oc (Pi - Po)Given the motor efficiency q :Po = q * Pi where:Q is heat dissipation rate (W)Pi is electrical input power (W)Attorney Docket No.: IS24.1111-WO-PCTPo is useful output power (W) r| is electrical efficiency

[0064] Substituting into the first equation:Q oc Pi * (1 - r|)

[0065] Introducing a proportionality constant k obtains:Q = k * Pi * (l - r|) (1)

[0066] Considering the basic electrical relation:P = I * V (2) where:V is voltageI is current

[0067] Combining (1) and (2) yields:

[0068] Assuming constant voltage and efficiency, the heat dissipation rate becomes directly proportional to the current. Thus, for two different time intervals:Q1 / Q2 = I1 / I2 (3)

[0069] In ESP systems, heat transfer from the motor to the fluid occurs primarily via convection. The operating motor generates heat due to electrical losses, which is absorbed and transported by the flowing multiphase fluid (e.g., oil, water, and gas) within the wellbore and tubing. The convection heat transfer equation is:where:- Q is the heat transfer rate [W]- h is the convection heat transfer coefficient [W / m2K]- A is the surface area [m2]- Ts is the surface temperature of the solid [K]- Tf is the temperature of the fluid [K]

[0070] From the fluid's perspective, heat absorption results in a temperature increase governed by the change in internal energy, represented as:Attorney Docket No.: IS24.1111-WO-PCT where:- m is the mass flow rate [kg / s]- Cp is the specific heat capacity [J / kg K]- To is the final fluid temperature [K]- Ti is the initial fluid temperature [K]

[0071] In practice:- Ti is measured by a sensor located below the electric motor (e.g., fluid entering the system)- To is approximated by the motor thermocouple (representing fluid temperature after heat exchange, but not the motor's internal temperature)

[0072] Thus:To = Tmotor (Tm), Ti = Tpump intake (Tp)

[0073] Substituting into the heat transfer ratio for two time points:QI / Q2 = (ml / m2) * ((Tml - Tpl) / (Tm2 - Tp2)) (5)

[0074] Combining equations (3) and (5) gives: m2 = (12 / II) * ((Tml - Tpl) / (Tm2 - Tp2)) * ml (6)

[0075] This formulation enables estimation of relative changes in fluid mass rate over time based on current (I) and temperature (T) measurements. Equation (6) is not designed to calculate absolute flow rates, but rather to provide a technical indication of whether flow is increasing or decreasing. Because current, motor temperature, and pump intake temperature may be transmitted at high frequency from downhole sensors, this method offers a practical approach for real-time monitoring of flow dynamics in ESP systems.Exemplary Me thod

[0076] Figure 10 illustrates a flowchart of a di ital / smart method 1000 for determining a performance and / or diagnosing an operation of a well with an electrical submersible pump (ESP) therein (i.e., an ESP well), according to an embodiment. An illustrative order of the method 1000 is provided below; however, one or more portions of the method 1000 may be performed in a different order, simultaneously, repeated, or omitted. At least a portion of the method may be performed using a computing system.

[0077] The method 1000 may include receiving input data, as at 1005. The input data may be related to a completion in the well and / or a reservoir deliverability of the well. The input data mayAttorney Docket No.: IS24.1111-WO-PCT include a model of the well that includes electrical submersible pump (ESP) data in the well, vertical lift performance (VLP) data in the well, inflow performance relationship (IPR) data in the well, or a combination thereof. The ESP data may include an electrical current used by the ESP 410, a temperature of an intake 420 of the ESP 410, a temperature of a motor 430 of the ESP 410, or a combination thereof.

[0078] The method 1000 may also include generating an ESP curve based upon the input data, as at 1010. The ESP curve may include or show head, power, and efficiency versus production rate. An example of the ESP curve is shown in Figure 2.

[0079] The method 1000 may also include generating a nodal analysis plot based upon the input data and / or the ESP curve, as at 1015. An example of a nodal analysis curve without the effect of an ESP pump is shown in Figure 3. The effect of the ESP pump may be considered as a separate element of the system.

[0080] The method 1000 may also include determining a mechanical status of the well based upon the input data, the ESP curve, and / or the nodal analysis plot, as at 1020. The mechanical status of the well may include several elements describing the depth, dimensions, and / or components of the system. For example, the mechanical status may include well depth details such as total depth (TD), measured depth (MD), true vertical depth (TVD), a kick-off point, deviation data, or a combination thereof. The mechanical status may also or instead include casing and tubing information such as casing strings (e.g., surface, intermediate, production) with sizes and setting depths. The casing and tubing information may also include the tubing size, grade, and / or length. The mechanical status may also or instead include wellhead and completing components such as the wellhead type and pressure rating, packers, safety valves, flow control devices, and perforation intervals and zones. The mechanical status may also or instead include accessories and special equipment such as subsurface safety valves, downhole sensors, monitoring tools, or a combination thereof.

[0081] The method 1000 may also include determining a performance of the well based upon the input data, the ESP curve, the nodal analysis plot, the mechanical status of the well, or a combination thereof, as at 1025. The performance may be or include potential abnormalities and / or production optimization opportunities. For example, the performance may include a performance of the ESP. The performance of the ESP may be or include an efficiency of the ESP and / or potential effects of gas production from and mechanical degradation to the ESP. TheAttorney Docket No.: IS24.1111-WO-PCT mechanical degradation may be or include erosion, internal blockage, a broken shaft, or a combination thereof.

[0082] The performance may also or instead include a relationship between the well and a reservoir. The relationship may identify changes in a skin factor and / or consequences of pressure variations in the reservoir. The pressure variations may include or be in response to a waterflooding effect.

[0083] The performance may also or instead include a behavior of a tubing 440 and a wellhead 450 in the well (see Figure 4). The behavior may identify alterations in a produced fluid density and / or new surface flowline connections that impact a pressure at the wellhead 450.

[0084] The performance may also or instead include relative changes in a fluid flow rate out of the well based upon the ESP data, between two different times (e.g., first time and second time). Thus, it may be possible to estimate whether the production rate increases or decreases at the second time in relation to the first time. The increase or decrease of the fluid flow rate at the second time may be determined using equation (6) above. More particularly, the direction of the fluid flow rate may be determined based upon the electrical current at a first time and the second time, the temperature of the intake at the first and second times, the temperature of the motor at the first and second times, and the fluid flow rate at the first time. The relative changes may be determined without relying on direct flow measurements out of the well.

[0085] The method 1000 may also include displaying the performance, as at 1030.

[0086] The method 1000 may also include performing a wellsite action in response to the performance, as at 1035. The wellsite action may be or include generating and / or transmitting a signal (e.g., using a computing system) that recommends, instructs, or causes a physical action to occur at a wellsite. The wellsite action may also or instead include performing the physical action at the wellsite. The physical action may include selecting where to drill a wellbore, drilling the wellbore, varying a weight and / or torque on a drill bit that is drilling the wellbore, varying a drilling trajectory of the wellbore, varying a concentration and / or flow rate of a fluid pumped into the wellbore, or the like. The physical action may also or instead include repairing or replacing the ESP in response to the mechanical degradation, pumping fluid in the well to minimize the pressure variations and / or the pressure at the wellhead, modifying the electrical current and / or temperature of the ESP.Attorney Docket No.: IS24.1111-WO-PCTExemplary Computing System

[0087] In some embodiments, the methods of the present disclosure may be executed by a computing system. Figure 11 illustrates an example of such a computing system 1100, in accordance with some embodiments. The computing system 1100 may include a computer or computer system 1101 A, which may be an individual computer system 1101 A or an arrangement of distributed computer systems. The computer system 1101A includes one or more analysis modules 1102 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 1102 executes independently, or in coordination with, one or more processors 1104, which is (or are) connected to one or more storage media 1106. The processor(s) 1104 is (or are) also connected to a network interface 1107 to allow the computer system 1101 A to communicate over a data network 1109 with one or more additional computer systems and / or computing systems, such as 1101B, 1101C, and / or 1101D (note that computer systems 1101B, 1101C and / or 1101D may or may not share the same architecture as computer system 1101 A, and may be located in different physical locations, e.g., computer systems 1101 A and 1101B may be located in a processing facility, while in communication with one or more computer systems such as 1101C and / or 1101D that are located in one or more data centers, and / or located in varying countries on different continents).

[0088] A processor may include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.

[0089] The storage media 1106 may be implemented as one or more computer-readable or machine-readable storage media. Note that while in the example embodiment of Figure 11 storage media 1106 is depicted as within computer system 1101A, in some embodiments, storage media 1106 may be distributed within and / or across multiple internal and / or external enclosures of computing system 1101A and / or additional computing systems. Storage media 1106 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),Attorney Docket No.: IS24.1111-WO-PCTBLURAY® 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.

[0090] In some embodiments, computing system 1100 contains one or more method execution module(s) 1108. In the example of computing system 1100, computer system 1101 A includes the method execution module 1108. In some embodiments, a single method execution module may be used to perform some aspects of one or more embodiments of the methods disclosed herein. In other embodiments, a plurality of method execution modules may be used to perform some aspects of methods herein.

[0091] It should be appreciated that computing system 1100 is merely one example of a computing system, and that computing system 1100 may have more or fewer components than shown, may combine additional components not depicted in the example embodiment of Figure 11, and / or computing system 1100 may have a different configuration or arrangement of the components depicted in Figure 11. The various components shown in Figure 11 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.

[0092] 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.

[0093] 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 1100, Figure 11), and / or through manual control by a user who may makeAttorney Docket No.: IS24.1111-WO-PCT determinations regarding whether a given step, action, template, model, or set of curves has become sufficiently accurate for the evaluation of the subsurface three-dimensional geologic formation under consideration.

[0094] The foregoing description, for purposes 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

Attorney Docket No.: IS24.1111-WO-PCTCLAIMSWhat is claimed is:

1. A method for determining a performance of a well with an electrical submersible pump (ESP) therein, the method comprising: receiving input data related to the well; generating an ESP curve based upon the input data; generating a nodal analysis plot based upon the input data; determining a mechanical status of the well based upon the input data; and determining the performance of the well based upon the ESP curve, the nodal analysis plot, and the mechanical status of the well.

2. The method of claim 1, wherein the input data is related to a completion in the well and a reservoir deliverability of the well.

3. The method of claim 1, wherein the input data comprises a model of the well that includes ESP data in the well, vertical lift performance (VLP) data in the well, and inflow performance relationship (IPR) data in the well.

4. The method of claim 3, wherein the ESP data comprises an electrical current used by the ESP, a temperature of an intake of the ESP, and a temperature of a motor of the ESP.

5. The method of claim 1, wherein the ESP curve comprises head, power, and efficiency versus production rate.

6. The method of claim 1, wherein the nodal analysis plot corresponds to a depth of the ESP pump in the well.

7. The method of claim 1, wherein the performance comprises potential abnormalities and production optimization opportunities.Attorney Docket No.: IS24.1111-WO-PCT8. The method of claim 1, wherein the performance is related to the ESP, a relationship between the well and a surrounding reservoir, a behavior of a tubing and / or a wellhead in the well, relative changes in a fluid flow rate out of the well, or a combination thereof.

9. The method of claim 1, further comprising displaying the performance.

10. The method of claim 1, further comprising performing an action in response to the performance.

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 input data related to a well, wherein the well has an electrical submersible pump (ESP) therein; generating an ESP curve based upon the input data; generating a nodal analysis plot based upon the input data; determining a mechanical status of the well based upon the input data; and determining the performance of the well based upon the ESP curve, the nodal analysis plot, and the mechanical status of the well.

12. The computing system of claim 11, wherein the performance comprises a performance of the ESP, wherein the performance of the ESP comprises an efficiency of the ESP and potential effects of gas production from and mechanical degradation to the ESP, and wherein the mechanical degradation comprises erosion, internal blockage, a broken shaft, or a combination thereof.

13. The computing system of claim 11, wherein the performance comprises a relationship between the well and a reservoir, wherein the relationship identifies changes in a skin factor and / or consequences of pressure variations in the reservoir, and wherein the pressure variations comprise or are in response to a waterflooding effect.Attorney Docket No.: IS24.1111-WO-PCT14. The computing system of claim 11, wherein the performance comprises a behavior of a tubing and a wellhead in the well, wherein the behavior identifies alterations in a produced fluid density and / or new surface flowline connections that impact a pressure at the wellhead.

15. The computing system of claim 11, wherein the input data comprises ESP data in the well including an electrical current used by the ESP, a temperature of an intake of the ESP, and a temperature of a motor of the ESP, wherein the performance comprises relative changes in a fluid flow rate out of the well based upon the ESP data, wherein the fluid flow rate at a second time is determined based upon the electrical current at a first time and the second time, the temperature of the intake at the first and second times, the temperature of the motor at the first and second times, and the fluid flow rate at the first time, and wherein the relative changes are determined without relying on direct flow measurements out of the well.

16. 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 input data related to a well, wherein the well has an electrical submersible pump (ESP) therein, generating an ESP curve based upon the input data; generating a nodal analysis plot based upon the input data; determining a mechanical status of the well based upon the input data; and determining the performance of the well based upon the ESP curve, the nodal analysis plot, and the mechanical status of the well.

17. The non-transitory computer-readable medium of claim 16, wherein the performance comprises a performance of the ESP, wherein the performance of the ESP comprises an efficiency of the ESP and potential effects of gas production from and mechanical degradation to the ESP, and wherein the mechanical degradation comprises erosion, internal blockage, a broken shaft, or a combination thereof.Attorney Docket No.: IS24.1111-WO-PCT18. The non-transitory computer-readable medium of claim 17, wherein the performance comprises a relationship between the well and a reservoir, wherein the relationship identifies changes in a skin factor and / or consequences of pressure variations in the reservoir, and wherein the pressure variations comprise or are in response to a waterflooding effect.

19. The non-transitory computer-readable medium of claim 18, wherein the performance comprises a behavior of a tubing and a wellhead in the well, wherein the behavior identifies alterations in a produced fluid density and / or new surface flowline connections that impact a pressure at the wellhead.

20. The non-transitory computer-readable medium of claim 19, wherein the input data is related to a completion in the well and a reservoir deliverability of the well, wherein the input data comprises a model of the well that includes ESP data in the well, vertical lift performance (VLP) data in the well, and inflow performance relationship (IPR) data in the well, wherein the ESP data comprises an electrical current used by the ESP, a temperature of an intake of the ESP, and a temperature of a motor of the ESP, and wherein the performance comprises relative changes in a fluid flow rate out of the well based upon the ESP data, wherein the fluid flow rate at a second time is determined based upon the electrical current at a first time and the second time, the temperature of the intake at the first and second times, the temperature of the motor at the first and second times, and the fluid flow rate at the first time, and wherein the relative changes are determined without relying on direct flow measurements out of the well.

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