RESERVOIR SIMULATION SYSTEM AND METHOD

Abstract

The present disclosure describes an efficient process through which knowledge gleaned from prior reservoir simulations may be captured and applied to future simulations with or without user involvement. A plurality of reservoir simulation categories may be defined and stored to a database. In one embodiment, reservoir simulation data may be captured and analyzed in order to identify process steps and/or workflows for each category of stored reservoir simulations. Upon starting a new reservoir simulation, the system may identify the category of the simulation at issue and query the database in order to identify stored process steps and/or workflows applicable thereto. The stored process steps and/or workflows may then be applied to the new reservoir simulation automatically or by providing suggestions and/or recommendation to the user.

Description

BACKGROUND

[0001] Oilfield operations generate a great deal of electronic data. Such data may be used to access oilfield conditions and make decisions concerning future oilfield operations such as well planning, well targeting, well completions, production rates, and other operations and/or operating parameters. Often this information is used to determine when (and/or where) to drill new wells, re-complete existing wells, or alter oilfield production parameters.

[0002] Oilfield data may be collected using sensors positioned about the oilfield. For example, sensors on the surface may monitor seismic exploration activities, sensors in the drilling equipment may monitor drilling conditions, sensors in the wellbore may monitor fluid composition, sensors located along the flow path may monitor flow rates, and sensors at the processing facility may monitor fluids collected.

[0003] Computer modeling and simulation of oilfield data is a vital component of oil and gas exploration. Such systems typically conduct some form of computational processing upon acquired or simulated oilfield data and then export the processed data to one or more data visualization application(s) for review by authorized personnel. Such systems may also use a color mapping structure to generate graphic visualizations of acquired data in order to assist users in interpreting and analyzing the acquired data.

[0004] Known oilfield simulation platforms may require the reservoir engineer to build the initial model from scratch, enter/modify input parameters and then interpret the results based upon their individual experience. This process may be especially difficult for those users having limited experience in the field.

[0005] As such, there remains a need for a system, method and computer readable medium capable of assisting the user with the oilfield simulation process utilizing information captured from prior reservoir simulations.

SUMMARY

[0006] Accordingly, the present disclosure describes an efficient process through which knowledge gleaned from prior reservoir simulations may be captured and applied to future simulations with or without user involvement.

[0007] A plurality of reservoir simulation categories may be defined and stored to the database. In one embodiment, reservoir simulation categories may be defined using information such as the type of the reservoir at issue in the simulation, the type of the simulation being conducted, the objective(s) of the simulation, and/or the specific parameters utilized during the simulation. These information types may be utilized alone or in combination in order to categorize the simulation for future reference.

[0008] In one embodiment, reservoir simulation data may be captured and analyzed in order to identify process steps and/or workflows for each category of reservoir simulation stored by the system. Identified workflows may be cross-referenced by reservoir simulation category and applied to future reservoir simulations.

[0009] In one embodiment, the system is capable of capturing reservoir simulation data. In one embodiment, this may include capturing data relating to user keystrokes, mouse movements, vocal commands/conversations with other personnel, user eye movement, facial recognition and/or any other user interaction with the system deemed to be relevant to the workflow used during a reservoir simulation.

[0010] Upon starting a new reservoir simulation, the system may identify the category of the simulation at issue and query the database in order to identify stored process steps and/or workflows applicable thereto. The system may provide various query tools and graphic user interfaces (GUI) to facilitate the efficient retrieval of stored process steps and/or workflows. Database query results may be displayed upon a GUI for review by the user or retrieved automatically from the database.

[0011] Retrieved workflows may be applied to the new reservoir simulation with or without human involvement. In one embodiment, the system may provide an "automatic" and "assisted" mode selection option, whereby the user may indicate their desired level of involvement. In this example, if the user selects automatic mode, the system may automatically apply workflows from previous simulations to the new simulation. In this example, if the user selects assisted mode, the system may provide suggestions and/or recommendations concerning how to proceed with the simulation.

[0012] This summary is provided to introduce a selection of concepts in a simplified form that are further described herein. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

[0013] A more complete appreciation of the invention and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings; it being understood that the drawings contained herein are not necessarily drawn to scale and that the accompanying drawings provide illustrative implementations and are not meant to limit the scope of various technologies described herein; wherein:

[0014] FIG. 1.1 is an example oilfield survey operation being performed by a seismic truck.

[0015] FIG. 1.2 is an example oilfield drilling operation being performed by a drilling tool suspended by a rig and advanced into the subterranean formation.

[0016] FIG. 1.3 is an example oilfield wireline operation being performed by a wireline tool suspended by the rig and into the wellbore of FIG. 1.2.

[0017] FIG. 1.4 is an example oilfield operation being performed by a production tool deployed from the rig and into a completed wellbore for drawing fluid from the downhole reservoir into a surface facility.

[0018] FIG. 2.1 is an example oilfield seismic trace of the subterranean formation of FIG. 1.1.

[0019] FIG. 2.2 is an example oilfield core sample of the example formation shown in FIG. 1.2.

[0020] FIG. 2.3 is an example oilfield well log of the subterranean formation of FIG. 1.3.

[0021] FIG. 2.4 is an example simulation decline curve of fluid flowing through the example subterranean formation of FIG. 1.4.

[0022] FIG. 3 is a schematic view, partially in cross section, of an example oilfield operation having a plurality of data acquisition tools positioned at various locations along the oilfield operation for collecting data from the subterranean formation.

[0023] FIG. 4 is an example schematic view of an oilfield operation having a plurality of wellsites for producing hydrocarbons from the subterranean formation.

[0024] FIG. 5 is a flowchart diagram illustrating a reservoir simulation process of one example embodiment.

[0025] FIG. 6 is an example computer system that may be utilized in conjunction with one or more embodiments.

DETAILED DESCRIPTION

[0026] In the following description, numerous details are set forth to provide an understanding of the present invention. However, it will be understood by those skilled in the art that the inventions described herein may be practiced without these details and that numerous variations or modifications from the described embodiments may be possible.

[0027] The present disclosure describes embodiments of a method of conducting reservoir simulations, a computer readable medium for conducting reservoir simulations and a reservoir simulation system.

[0028] By way of background, FIGS. 1.1-1.4 illustrate simplified, schematic views of oilfield (100) having subterranean formation (102) containing reservoir (104) therein in accordance with implementations of various technologies and techniques described herein.

[0029] FIG. 1.1 illustrates a survey operation being performed by a survey tool, such as seismic truck (106.1), to measure properties of the subterranean formation. In this example, the survey operation is a seismic survey operation for producing sound vibrations. In FIG. 1.1, sound vibrations (112) generated by source (110), reflects off horizons (114) in earth formation (116). A set of sound vibrations is received by sensors, such as geophone-receivers (118), situated on the earth's surface. The data received (120) is provided as input data to a computer (122.1) of a seismic truck (106.1), and responsive to the input data, computer (122.1) generates seismic data output (124). This seismic data output may be stored, transmitted or further processed as desired, for example, by data reduction.

[0030] FIG. 1.2 illustrates a drilling operation being performed by drilling tool (106.2) suspended by rig (128) and advanced into subterranean formations (102) to form wellbore (136). Mud pit (130) is used to draw drilling mud into the drilling tools via flow line (132) for circulating drilling mud down through the drilling tools, then up wellbore (136) and back to the surface. The drilling mud may be filtered and returned to the mud pit.

[0031] A circulating system may be used for storing, controlling, or filtering the drilling mud. The drilling tools are advanced into subterranean formations (102) to reach reservoir (104). Each well may target one or more reservoirs. The drilling tools may be adapted for measuring downhole properties using logging while drilling tools. The logging while drilling tools may also be adapted for taking core sample (133).

[0032] Computer facilities may be positioned at various locations about the oilfield (100) (e.g., the surface unit 134) and/or at remote locations. Surface unit (134) may be used to communicate with the drilling tools and/or offsite operations, as well as with other surface or downhole sensors. Surface unit is capable of communicating with the drilling tools to send commands to the drilling tools, and to receive data therefrom. Surface unit may also collect data generated during the drilling operation and produces data output (135), which may then be stored or transmitted.

[0033] Sensors (S), such as gauges, may be positioned about oilfield (100) to collect data relating to various oilfield operations as described previously. In this example, sensor (S) may be positioned in one or more locations in the drilling tools and/or at rig (128) to measure drilling parameters, such as weight on bit, torque on bit, pressures, temperatures, flow rates, compositions, rotary speed, and/or other parameters of the field operation. Sensors (S) may also be positioned in one or more locations in the circulating system.

[0034] Drilling tools (106.2) may include a bottom hole assembly (BHA) (not shown) near the drill bit (e.g., within several drill collar lengths from the drill bit). The bottom hole assembly may include capabilities for measuring, processing, and storing information, as well as communicating with the surface unit. The bottom hole assembly further may further include drill collars for performing various other measurement functions.

[0035] The data gathered by sensors (S) may be collected by the surface unit and/or other data collection sources for analysis or other processing. The data collected by sensors (S) may be used alone or in combination with other data. The data may be collected in one or more databases and/or transmitted on or offsite. The data may be historical data, real time data, or combinations thereof. The real time data may be used in real time, or stored for later use. The data may also be combined with historical data or other inputs for further analysis. The data may be stored in separate databases, or combined into a single database.

[0036] Surface unit (134) may include transceiver (137) to allow communications between surface unit (134) and various portions of the oilfield (100) or other locations. The surface unit may also be provided with one or more controllers (not shown) for actuating mechanisms at the oilfield. The surface unit may then send command signals to the oilfield in response to data received.

[0037] The surface unit may receive commands via transceiver (137) or may itself execute commands to the controller. A processor may be provided to analyze the data (locally or remotely), make the decisions and/or actuate the controller. In this manner, the oilfield may be selectively adjusted based on the data that is collected and analyzed. This technique may be used to optimize portions of the field operation, such as controlling drilling, weight on bit, pump rates, or other parameters. These adjustments may be made automatically based on computer protocol, and/or manually by an operator. In some cases, well plans may be adjusted to select optimum operating conditions, or to avoid problems.

[0038] FIG. 1.3 illustrates a wireline operation being performed by wireline tool (106.3) suspended by rig (128) and into wellbore (136) of FIG. 1.2. The wireline tool may be adapted for deployment into the wellbore for generating well logs, performing downhole tests and/or collecting samples. The wireline tool may be used to provide another method and apparatus for performing a seismic survey operation. The wireline tool may, for example, have an explosive, radioactive, electrical, or acoustic energy source (144) that sends and/or receives electrical signals to surrounding subterranean formations (102) and fluids therein.

[0039] Wireline tool (106.3) may be operatively connected to, for example, geophones (118) and a computer (122.1) of a seismic truck (106.1) of FIG. 1.1. Wireline tool (106.3) may also provide data to surface unit (134). Surface unit (134) may collect data generated during the wireline operation and may produce data output (135) that may be stored or transmitted and subsequently analyzed. Wireline tool (106.3) may be positioned at various depths in the wellbore (136) to provide information relating to the subterranean formation (102).

[0040] Sensors (S), such as gauges, may be positioned about oilfield (100) to collect data relating to various field operations as described previously. Sensors may be positioned in wireline tool (106.3) to measure downhole parameters which relate to, for example porosity, permeability, fluid composition and/or other parameters of the oilfield operation.

[0041] FIG. 1.4 illustrates a production operation being performed by production tool (106.4) deployed from a production unit or Christmas tree (129) and into completed wellbore (136) for drawing fluid from the downhole reservoirs into surface facilities (142). The fluid flows from reservoir (104) through perforations in the casing (not shown) and into production tool (106.4) in wellbore (136) and to surface facilities (142) via gathering network (146).

[0042] Sensors, such as gauges, may be positioned about oilfield (100) to collect data relating to various field operations as described previously. Sensors may be positioned in production tool (106.4) or associated equipment, such as Christmas tree (129), gathering network (146), surface facility (142), and/or the production facility, to measure fluid parameters, such as fluid composition, flow rates, pressures, temperatures, and/or other parameters of the production operation.

[0043] Production may also include injection wells for added recovery. One or more gathering facilities may be operatively connected to one or more of the wellsites for selectively collecting downhole fluids from the wellsite(s).

[0044] While FIGS. 1.2-1.4 illustrate tools used to measure data relating to an oilfield, it will be appreciated that the tools may be used in connection with non-oilfield operations, such as gas fields, mines, aquifers, storage, or other subterranean facilities. Also, while certain data acquisition tools are depicted, it will be appreciated that various measurement tools capable of sensing parameters, such as seismic two-way travel time, density, resistivity, production rate, etc., of the subterranean formation and/or its geological formations may be used. Various sensors (S) may be located at various positions along the wellbore and/or the monitoring tools to collect and/or monitor the desired data. Other sources of data may also be provided from offsite locations.

[0045] FIGS. 2.1-2.4 are example graphical depictions of data collected by the tools of FIGS. 1.1-1.4. FIG. 2.1 depicts a seismic trace (202) of the subterranean formation of FIG. 1.1 taken by survey truck (106.1). The seismic trace measures a two-way response over a period of time. FIG. 2.2 depicts a core sample (233) taken by the drilling tool (106.2). The core test may provide a graph of the density, resistivity, or other physical property of the core sample (233) over the length of the core. Tests for density and viscosity may be performed on the fluids in the core at varying pressures and temperatures. FIG. 2.3 depicts a well log (204) of the subterranean formation of FIG. 1.3 taken by the wireline tool (106.3). The wireline log typically provides a resistivity measurement of the formation at various depths. FIG. 2.4 depicts a production decline curve (206) of fluid flowing through the subterranean formation of FIG. 1.4 taken by the production tool (106.4). The production decline curve (206) may provide the production rate Q as a function of time t.

[0046] The respective graphs of FIGS. 2.1-2.3 contain static measurements that describe the physical characteristics of the formation. These measurements may be compared to determine the accuracy of the measurements and/or for checking for errors. In this manner, the plots of each of the respective measurements may be aligned and scaled for comparison and verification of the properties.

[0047] FIG. 2.4 provides a dynamic measurement of the fluid properties through the wellbore. As the fluid flows through the wellbore, measurements are taken of fluid properties, such as flow rates, pressures, composition, etc. As described below, the static and dynamic measurements may be used to generate models of the subterranean formation to determine characteristics thereof.

[0048] FIG. 3 is a schematic view, partially in cross section of an oilfield (300) having data acquisition tools (302A), (302B), (302C), and (302D) positioned at various locations along the oilfield for collecting data of a subterranean formation (304). The data acquisition tools (302A-302D) may be the same as data acquisition tools of FIG. 1, respectively. In this example, the data acquisition tools (302A-302D) may generate data plots or measurements (308A-308D), respectively.

[0049] Data plots (308A-308D) are examples of static data plots that may be generated by the data acquisition tools (302A-302D), respectively. Static data plot (308A) is a seismic two-way response time and may be the same as the seismic trace (202) of FIG. 2.1. Static plot (308B) is core sample data measured from a core sample of the formation (304), similar to the core sample (233) of FIG. 2.2. Static data plot (308C) is a logging trace, similar to the well log (204) of FIG. 2.3. Data plot (308D) is a dynamic data plot of the fluid flow rate over time, similar to the graph (206) of FIG. 2.4. Other data may also be collected, such as historical data, user inputs, economic information, other measurement data, and other parameters of interest.

[0050] The subterranean formation (304) has a plurality of geological structures (306A-306D). In this example, the formation has a sandstone layer (306A), a limestone layer (306B), a shale layer (306C), and a sand layer (306D). A fault line (307) extends through the formation. The static data acquisition tools may be adapted to measure the formation and detect the characteristics of the geological structures of the formation.

[0051] While a specific subterranean formation (304) with specific geological structures are depicted, it will be appreciated that the formation may contain a variety of geological structures. Fluid may also be present in various portions of the formation. Each of the measurement devices may be used to measure properties of the formation and/or its underlying structures in order to generate oilfield data. While each acquisition tool is shown as being in specific locations along the formation, it will be appreciated that one or more types of measurement may be taken at one or more location across one or more oilfields or other locations for comparison and/or analysis.

[0052] The data collected from various sources, such as the data acquisition tools of FIG. 3, may then be evaluated using one or more data visualization applications. Seismic data displayed in the static data plot (308A) from the data acquisition tool (302A) may be used by a geophysicist to determine characteristics of the subterranean formation (304). Core data shown in static plot (308B) and/or log data from the well log (308C) may be used by a geologist to determine various characteristics of the geological structures of the subterranean formation (304). Production data from the production graph (308D) may be used by the reservoir engineer to determine fluid flow and reservoir characteristics.

[0053] FIG. 4 illustrates an example oilfield (400) for performing oilfield operations. In this example, the oilfield has a plurality of wellsites (402) operatively connected to a central processing facility (454). Part or all of the oilfield may be on land and/or sea. Also, while a single oilfield with a single processing facility and a plurality of wellsites is depicted, any combination of one or more oilfields, one or more processing facilities and one or more wellsites may be present.

[0054] Each wellsite (402) may have equipment that forms a wellbore (436) into the earth. The wellbores extend through subterranean formations (406) including reservoirs (404). These reservoirs (404) contain fluids, such as hydrocarbons. The wellsites draw fluid from the reservoirs and pass them to the processing facilities via surface networks (444). The surface networks (444) may have tubing and control mechanisms for controlling the flow of fluids from the wellsite to the processing facility (454).

[0055] Referring to FIG. 5, the present disclosure describes a system, method, and computer readable medium for conducting reservoir simulations. Specifically, the present disclosure describes an efficient process through which knowledge gleaned from prior reservoir simulations may be captured and applied to future simulations.

[0056] In one embodiment, one or more computer databases (500) may be utilized for storing reservoir simulation data (505) relating to one or more oilfield operations (510). A plurality of reservoir simulation categories may be defined and stored to the database, as illustrated by Box (515). In one embodiment, reservoir simulation categories may be defined using information such as the type of the reservoir at issue in the simulation, the type of the simulation being conducted, the objective(s) of the simulation, and/or the specific parameters utilized during the simulation. These information types may be utilized alone or in combination in order to categorize the simulation for future reference.

[0057] The reservoir simulation categories described herein may be utilized to store and/or retrieve process steps and/or workflows pertaining to certain type(s) of reservoir simulations for future use. In one embodiment, the reservoir type may include information concerning the properties of the reservoir. In this example, the properties of the reservoir may include information such as the fluids present, rock properties, porosity information, permeability information, oil content, gas content, water saturation, temperature gradients, pressure gradients, etc. This information may be reflected by the system using one or more codes. For example, a fluid type code may be used to indicate fluid types, porosity type codes may be used to indicate porosity types, an average net pay code may be used to indicate the amount of oil present in the reservoir, etc.

[0058] In one embodiment, geological characteristics of the reservoir may be utilized in order to categorize the reservoir simulation according to reservoir type. For example, the geological characteristics of the reservoir may include information such as the geometry of the reservoir, structural/stratigraphic characteristics of the reservoir (faults, etc), and/or depositional/sedimental characteristics of the reservoir (alluvial-fan, fluvial, Eolian, delta systems, barrier bars, shelf, slope, basinal, etc).

[0059] Geological information concerning the reservoir may be reflected by the system using one or more codes. For example, a lithology code may be used to indicate the relative lithology of the reservoir, a tectonics code may be utilized to indicate the relative tectonic characteristics of the reservoir, etc.

[0060] In one embodiment, the simulation type may indicate the type of simulation at issue. In this example, the simulation type may indicate whether the simulation is a black oil, compositional, thermal, etc., type of simulation and/or a history matching, well location optimization, production optimization, enhanced oil recovery, etc., type of simulation. The objective(s) of the simulation may also be utilized in order to categorize the reservoir simulation. For example, in the context of a history matching simulation, the objective of the simulation may be to obtain a matching result with respect to certain parameters, such as the oil rate, the water rate, etc.

[0061] In one embodiment, simulation parameters may also be utilized in order to categorize the reservoir simulation. Simulation parameters may include anything of interest to the simulation, including the type of optimization algorithm(s), the type of permeability curve(s), etc. For example, in a reservoir simulation having a sloped geological environment, simulation parameters such as the slope thickness, areal distribution, vertical distribution, etc., may be utilized. In an example reservoir having a fluvial geological environment, reservoir simulation parameters such as the sinuosity of the channel, the channel ratio, etc, may be utilized. For an example reservoir containing an aquifer, simulation parameters may include aquifer related parameters, such as aquifer strength, aquifer type, aquifer location (side, bottom), etc.

[0062] In one embodiment, reservoir simulation data may be captured and analyzed in order to identify process steps and/or workflows for each category of reservoir simulation stored by the system, as illustrated by Boxes (520) and (525) of FIG. 5. In one embodiment, a workflow may include a plurality of reservoir simulation process steps. Identified workflows may be cross-referenced by reservoir simulation category and applied to future reservoir simulations.

[0063] In one embodiment, the system is capable of capturing reservoir simulation data. In one embodiment, this may include capturing data relating to user keystrokes, mouse movements, vocal commands/conversations with other personnel, user eye movement and/or any other user interaction with the system deemed to be relevant to the workflow used during a reservoir simulation.

[0064] Reservoir simulation data may be gleaned from previously stored reservoir simulations (such as those stored upon database (500)) and/or captured in real time (or near real time) during reservoir simulations performed by one or more example users (530) using example computer (535).

[0065] Direct commands made by the user (via keystroke, mouse movement, verbal commands, etc) may be captured and stored by the system. For example, if the user desires to enter a direct statement such as "for reservoir type "A" I don't want a pressure value greater than 200 psi," he or she can enter the command via the keyboard or speak the appropriate command. The command may then be captured by the system and applied to the rest of his or her simulation. Further, any direct commands may be stored for use with subsequent simulations having similar reservoir characteristics.

[0066] In one embodiment, a computer utilized by a user during a reservoir simulation may be equipped with an eye tracking module (540) capable of tracking and recording the user's eye movements during a simulation. The eye tracking module may include hardware, software, or a combination thereof. User eye movements during the simulation may be cross-referenced with other actions taken by the user (keystrokes, mouse movement, etc.) along with events occurring upon the computer screen in order to capture the process steps taken by the user during the simulation and apply the process steps (or workflows) to future simulations having similar characteristics.

[0067] Consider a situation where a user is looking at a visualization of a reservoir upon his or her computer screen during a history matching simulation involving a reservoir having an aquifer. In this example, the user is likely to look at certain portions of the displayed reservoir in order to access the parameters (or ranges of parameters) that he or she needs to use during the simulation. In this example, the user may decide to generate a graphical display of the pressure field around the aquifer in order to access the impact of the aquifer upon the pressure distribution of the reservoir.

[0068] In this example, the eye tracking functionality of the system is capable of capturing and cross referencing the eye movements of the user with events on screen in order to capture the workflow used by the user during the simulation. Thus, in this example, the system utilizes eye tracking technology to track the process steps taken by the user in connection with a reservoir simulation involving a reservoir having an aquifer and a history matching simulation type.

[0069] The eye tracking functionality described herein may be applied to the results portion of the simulation as well. Consider a situation where the user has completed the simulation and is reviewing the results upon his or her computer screen. The user may look at certain portions of the computer screen in order to ascertain the success (or lack thereof) of the simulation. In this example, the eye tracking functionality of the system is capable of capturing and cross referencing the eye movements of the user with events on screen in order to capture the workflow used by the user during the "results phase" of the simulation.

[0070] In one embodiment, data gleaned from eye tracking may be utilized in order to generate one or more maps (not shown) illustrating the important portions of the displayed data during a reservoir simulation. In the simplified example above, a first map could be generated to indicate the relative importance of the displayed data relating the pressure profile around the aquifer and a second map could be generated to indicate the relative importance of the simulation results.

[0071] In one embodiment, a color scheme could be utilized to denote areas of user eye concentration upon the screen. For example, areas of high concentration could be denoted with a red color, areas of middle concentration could be denoted with a yellow color, while areas with a low concentration could be denoted with a green color. Data gleaned from eye tracking may also be utilized to highlight one or more portions of the display screen during subsequent simulations in order to indicate their relative importance.

[0072] In one embodiment, audio capture functionality capable of tracking and recording the user's verbal commands and/or conversations during a simulation may be utilized. In one embodiment, the user's computer may be equipped with audio capture hardware, such as a microphone (545) and software having Natural Language Processing (NLP) capability.

[0073] User conversations and/or voice commands during the simulation may be cross-referenced with other actions taken by the user (keystrokes, mouse movement, etc.) along with events upon the computer screen in order to capture the process steps taken by the user during the simulation and apply the process steps (or workflows) to future simulations having similar characteristics.

[0074] Consider the above example where a user is conducting a history matching of a reservoir simulation model with an aquifer. In this example, audio commands made by the user during the simulation may be captured by the microphone and processed by the NLP software. Further, voice commands made by other personnel (such as a supervisor discussing the simulation with the user) may be recorded and used to identify simulation process steps and/or workflows.

[0075] Consider an example where the user discusses a field pressure simulation parameter with his or her supervisor during a reservoir simulation. In this example, the system may capture the conversation and cross reference it with the actions taken by the user subsequent to the conversation in order to identify appropriate process steps and/or workflows relating to the field pressure parameter given the characteristics of the simulation.

[0076] In one embodiment, the system (in conjunction with the NLP software) may generate IF/THEN rules/statements utilizing the captured audio information for use during future simulations having similar characteristics. For example, if the system captures a conversation between the user and their supervisor where the user asks if a well injection pressure of 100 psi is appropriate for a certain type of reservoir and the supervisor says "No, you need to increase the well injection pressure to at least 200 psi for that type of reservoir," the system may record this exchange and convert it to IF/THEN rules/statements indicating that 200 psi or greater would be preferred for future simulations having similar characteristics.

[0077] Another example of verbal communication involving a reservoir having an aquifer with excessive water production could read along the lines of the following: "Do you have an aquifer defined on the data deck? Normally the rule of thumb is to have an aquifer 20 to 30 times bigger than the reservoir volume you have . . . check the relationship aquifer-reservoir you have. If this is too high (bigger than 30 times) aquifer will be very strong and you will have a lot of water production. Another thing you can try is to increase porosity between the water zone and the wells. As you have more rock volume, it will take more time for the water to fill the cells and therefore to breakthrough in the wells."

[0078] In this example, the system may capture the conversation and analyze it to identify the important aspect(s) of the conversation. In this example, the system may identify that the aquifer should be 20 to 30 times bigger than the reservoir volume and that this information should be considered when defining aquifer parameters. Further, the system may automatically fashion IF/THEN rules/statements from the captured conversation:

[0079] 1) IF we have water production above "X" amount, THEN the aquifer size might be the problem. THEN reduce aquifer size if you get excessive water production.

[0080] 2) IF point #1 does not solve the problem, THEN increase porosity between water zone and one or more wells.

[0081] In one embodiment, facial recognition software may be used (in connection a suitable camera or other video device) to identify each user providing input on a reservoir simulation. This feature allows the system to track where captured data comes from and provide that information to subsequent users where appropriate.

[0082] In the field pressure example above, the facial recognition functionality allows the system to identify who is speaking in the captured audio conversation and access their skills/experience prior to inclusion in the identified workflow(s). The system may provide this information to future users in connection with their simulation, i.e., "Supervisor John Doe indicated that a field pressure of greater than 200 psi should be utilized in connection with a history matching simulation for a reservoir of category `A` having at least one aquifer."

[0083] In one embodiment, each process step and/or workflow may be associated with one or more reservoir simulation categories and stored to the database, as illustrated by Boxes (550) and (555) of FIG. 5. This may be accomplished using metadata or other suitable data storage conventions. This feature allows stored process steps and/or workflows to be matched to a particular simulation category, retrieved via query tool(s) and applied to future reservoir simulations.

[0084] The system may also track run-time options, convergence and speed-up modifications and/or any errors encountered during the simulation(s). A goodness of simulation measure may be considered in accessing the results of the captured simulation. For example, in a history matching study, the goodness of simulation may utilize the misfit value of a production data parameter. In this example, the misfit value may be the difference between simulated and field observation(s) for one or more outputs of the reservoir model. In a thermal simulation, the goodness of simulation may utilize values such as the steam oil ratio or the temperature profile around a well. If the user makes any changes to improve the goodness of simulation, the action (e.g. changing the number or position of inflow control devices) may be recorded along with the goodness of simulation value and applied to future simulations as appropriate.

[0085] The system may utilize one or more learning algorithms during the reservoir simulation data capture process. In one embodiment, supervised and unsupervised learning algorithms may be utilized alone or on combination. In one embodiment, a supervised learning algorithm may utilize label data as a training data set whereas an unsupervised learning algorithm would not require the use of such data.

[0086] Upon starting a new reservoir simulation, the system may identify the category of the simulation at issue and query the database in order to identify stored process steps and/or workflows applicable thereto, as illustrated by Boxes (560), (565) and (570) of FIG. 5. The system may provide various query tools and graphic user interfaces to facilitate the efficient retrieval of stored process steps and/or workflows. Database query results may be displayed upon a GUI for review by the user or retrieved automatically from the database, as illustrated by Box (575) of FIG. 5. The system may be pre-programmed with default thresholds indicating whether process steps and/or workflow(s) from prior simulation(s) substantially match the new simulation. In one embodiment, such thresholds may be altered according to user preferences.

[0087] In one embodiment, a ranking feature may be utilized whereby the system ranks the retrieved process steps/workflows according to the number of similarities between the reservoir at issue and the reservoirs of the stored workflows. For example, the system may retrieve multiple sets of stored workflows and rank them by a degree of similarity with respect to reservoir type, simulation type, simulation objectives and simulation parameters.

[0088] In this example, the degree of similarity may be determined according to how many reservoir categories, simulation categories, and/or parameter categories the current simulation has in comparison to the reservoirs of the stored workflows. In one embodiment, the system may use a GUI to illustrate the retrieved workflows and provided details as to their previous application. For example, the GUI may show a list of retrieved workflows ranked according to reservoir similarity, where the workflow was used previously, etc., such that the user may select which workflow he or she wishes to apply to their current simulation. Further, the system may provide a GUI through which the user may indicate that he or she wishes to emphasize a particular type of reservoir, simulation and/or parameter type.

[0089] Upon reviewing the query results, the user may select one or more of the identified process steps and/or workflows associated with the simulation at issue. He or she may also be given the option to change the order or parameters of the displayed process steps as desired. Upon selection by the user, the selected process steps and/or workflows may be applied to the reservoir simulation and the results displayed to the user, as illustrated by Box (580) of FIG. 5. In one embodiment, the system allows the user to amend and/or revise the process steps and/or workflows to be performed via a suitable graphic user interface. In some cases, this may require entry of additional process steps and/or workflows, such as custom operations, into the system.

[0090] In one embodiment, the database may include historical information regarding each process step or workflow. Historical information may include information such as when and where stored process steps/workflows have been used, the number of times they have been used, the simulation categories they have been used with during past simulations, etc. Historical information may be stored upon the database and presented to the user when he or she interacts with the system. In one embodiment, a balloon or box (not shown) may be displayed to the user adjacent to a process step and/or workflow. This feature helps the user determine the applicability and/or reliability of the process step(s) and/or workflows in question for their particular simulation.

[0091] Retrieved workflows may be applied to the new reservoir simulation with or without human involvement. In one embodiment, the system may provide an "automatic" and "assisted" mode selection option, whereby the user may indicate their desired level of involvement. In this example, if the user selects automatic mode, the system may automatically apply workflows from previous simulations to the new simulation. This feature may involve automatic population of one or more of the parameter fields of the new simulation.

[0092] In one embodiment, the user may refine reservoir simulations using a styling interface (585). In one embodiment, a unique styling interface may be provided for each reservoir simulation category in order to allow the user to adjust how the simulation is displayed.

[0093] In one embodiment, user selections and/or styling preferences may be stored for later projects. For example, if a user has selected parameters and styling preferences for a particular reservoir simulation category, the system may store preference information for the user and/or project in question and apply it to later sessions. In one embodiment, stored selections and/or styling data may be stored and applied to subsequent sessions according to reservoir simulation category, such that the user's next encounter with a particular type of reservoir simulation may automatically be populated with the user's preferences.

[0094] The system may provide customization options whereby the user may amend default process steps and/or workflows by entering and/or importing custom preferences and/or customized reservoir simulation types. In one embodiment, this may be accomplished using one or more customization screens (not shown). This feature may also be used to allow the user to enter custom process steps and/or workflows so that highly trained users may tailor the system to their specifications.

[0095] The system, method and computer readable medium described herein may be utilized in conjunction with any suitable reservoir simulation types and the inventions described herein are not limited to use with the example reservoir simulation types or example process steps and/or workflows. Further, the inventions described herein may be used at any phase of an oilfield operation including, but not limited to, during the interpretation of seismic data, during modeling of formational characteristics or reservoir properties (including surface modeling), and/or during operational monitoring and analysis activities.

[0096] The methods described herein may be implemented on any suitable computer system capable of processing electronic data. FIG. 6 illustrates one possible configuration of a computer system (590) that may be utilized. Computer system(s), such as the example system of FIG. 6, may run programs containing instructions, that, when executed, perform methods according to the principles described herein. Furthermore, the methods described herein may be fully automated and able to operate continuously, as desired.

[0097] The computer system may utilize one or more central processing units (595), memory (600), communications or I/O modules (605), graphics devices (610), a floating point accelerator (615), and mass storage devices such as tapes and discs (620). Storage device (620) may include a floppy drive, hard drive, CD-ROM, optical drive, or any other form of storage device. In addition, the storage devices may be capable of receiving a floppy disk, CD-ROM, DVD-ROM, disk, flash drive or any other form of computer-readable medium that may contain computer-executable instructions.

[0098] Further, communication device (605) may be a modem, network card, or any other device to enable communication to receive and/or transmit data. It should be understood that the computer system (590) may include a plurality of interconnected (whether by intranet or Internet) computer systems, including without limitation, personal computers, mainframes, PDAs, cell phones and the like.

[0099] It should be understood that the various technologies described herein may be implemented in connection with hardware, software or a combination of both. Thus, various technologies, or certain aspects or portions thereof, may take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the various technologies.

[0100] In the case of program code execution on programmable computers, the computing device may include a processor, a storage medium readable by the processor (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. One or more programs that may implement or utilize the various technologies described herein may use an application programming interface (API), reusable controls, and the like.

[0101] Such programs may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) may be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language, and combined with hardware implementations.

[0102] The computer system (590) may include hardware capable of executing machine readable instructions, as well as the software for executing acts that produce a desired result. In addition, computer system (590) may include hybrids of hardware and software, as well as computer sub-systems.

[0103] Hardware may include at least processor-capable platforms, such as client-machines (also known as personal computers or servers), and hand-held processing devices (such as smart phones, personal digital assistants (PDAs), or personal computing devices (PCDs), for example). Further, hardware may include any physical device that is capable of storing machine-readable instructions, such as memory or other data storage devices. Other forms of hardware include hardware sub-systems, including transfer devices such as modems, modem cards, ports, and port cards, for example.

[0104] Software includes any machine code stored in any memory medium, such as RAM or ROM, and machine code stored on other devices (such as floppy disks, flash memory, or a CD ROM, for example). Software may include source or object code, for example. In addition, software encompasses any set of instructions capable of being executed in a client machine or server.

[0105] A database may be any standard or proprietary database software, such as Oracle, Microsoft Access, SyBase, or DBase II, for example. The database may have fields, records, data, and other database elements that may be associated through database specific software. Additionally, data may be mapped. Mapping is the process of associating one data entry with another data entry. For example, the data contained in the location of a character file can be mapped to a field in a second table. The physical location of the database is not limiting, and the database may be distributed. For example, the database may exist remotely from the server, and run on a separate platform.

[0106] Further, the computer system may operate in a networked environment using logical connections to one or more remote computers. The logical connections may be any connection that is commonplace in offices, enterprise-wide computer networks, intranets, and the Internet, such as local area network (LAN) and a wide area network (WAN). The remote computers may each include one or more application programs.

[0107] When using a LAN networking environment, the computer system may be connected to the local network through a network interface or adapter. When used in a WAN networking environment, the computer system may include a modem, wireless router or other means for establishing communication over a wide area network, such as the Internet.

[0108] The modem, which may be internal or external, may be connected to the system bus via the serial port interface. In a networked environment, program modules depicted relative to the computer system, or portions thereof, may be stored in a remote memory storage device.

[0109] Although the invention has been described with reference to specific embodiments, this description is not meant to be construed in a limited sense. Various modifications of the disclosed embodiments, as well as alternative embodiments of the invention, will become apparent to persons skilled in the art upon reference to the description of the invention. It is, therefore, contemplated that the appended claims will cover such modifications that fall within the scope of the invention.

Claims

1. A computer implemented method for conducting reservoir simulations comprising: identifying one or more workflows utilized in connection with one or more reservoir simulations; storing the identified workflows to a computer database; and applying at least one of the identified workflows to a subsequent reservoir simulation.

2. The computer implemented method of claim 1, wherein the workflows comprise a plurality of reservoir simulation process steps.

3. The computer implemented method of claim 1, wherein one or more of the workflows are identified using voice recognition or eye tracking.

4. The computer implemented method of claim 1, wherein one or more of the identified workflows are associated with one or more reservoir simulation categories.

5. The computer implemented method of claim 1, further comprising: determining a reservoir simulation category associated with the identified workflow and the subsequent reservoir simulation; and wherein the reservoir simulation category of the identified workflow substantially matches the reservoir simulation category of the subsequent reservoir simulation.

6. The computer implemented method of claim 5, wherein the reservoir simulation category further comprises a reservoir type, a simulation type, and one or more simulation parameters.

7. The computer implemented method of claim 6, wherein the reservoir type further comprises fluid, porosity and permeability properties of the reservoir.

8. The computer implemented method of claim 6, wherein the reservoir type further comprises a plurality of geological properties of the reservoir.

9. The computer implemented method of claim 6, wherein the simulation type comprises a history matching simulation or a thermal simulation.

10. The computer implemented method of claim 1, wherein at least one of the identified workflows are applied to the subsequent reservoir simulation by providing recommendations to a user.

11. The computer implemented method of claim 1, wherein at least one of the identified workflows are applied to the subsequent reservoir simulation automatically without user intervention.

12. A reservoir simulation system comprising: a processor operative to: identify one or more workflows utilized in connection with one or more reservoir simulations; store the identified workflows to a computer database; and apply at least one of the identified workflows to a subsequent reservoir simulation, wherein at least one reservoir simulation category associated with the identified workflow substantially matches at least one reservoir simulation category associated with the subsequent reservoir simulation.

13. The reservoir simulation system of claim 12, wherein one or more of the workflows are identified using voice recognition or eye tracking.

14. The reservoir simulation system of claim 12, wherein the reservoir simulation categories further comprise reservoir type, simulation type, and simulation parameters.

15. The reservoir simulation system of claim 12, wherein the identified workflows are applied to the subsequent reservoir simulation by providing recommendations to a user.

16. The reservoir simulation system of claim 12, wherein the identified workflows are applied to the subsequent reservoir simulation automatically without user intervention.

17. A non-transitory computer readable medium for conducting reservoir simulations comprising instructions which, when executed, cause a computing device to: identifying one or more workflows utilized in connection with one or more reservoir simulations; storing the identified workflows to a computer database; determining a reservoir simulation category associated with the identified workflow and a subsequent reservoir simulation; and applying at least one of the identified workflows to a subsequent reservoir simulation, wherein the reservoir simulation category of the identified workflow substantially matches the reservoir simulation category of the subsequent reservoir simulation.

18. The computer readable medium of claim 17, wherein the reservoir simulation category further comprises a reservoir type, a simulation type, and one or more simulation parameters.

19. The computer readable medium of claim 18, wherein the reservoir type further comprises a plurality of geological properties of the reservoir.

20. The computer readable medium of claim 18, wherein the simulation type comprises a history matching simulation or a thermal simulation.

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