US20090125362A1 - Systems and Methods For Workflow Automation, Adaptation and Integration - Google Patents
Systems and Methods For Workflow Automation, Adaptation and Integration Download PDFInfo
- Publication number
- US20090125362A1 US20090125362A1 US12/266,766 US26676608A US2009125362A1 US 20090125362 A1 US20090125362 A1 US 20090125362A1 US 26676608 A US26676608 A US 26676608A US 2009125362 A1 US2009125362 A1 US 2009125362A1
- Authority
- US
- United States
- Prior art keywords
- application
- another
- workflow
- technical application
- technical
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0633—Workflow analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
Definitions
- the present invention generally relates to systems and methods for implementing complex and disparate workflows and, more particularly, a flexible framework for workflow automation, adaptation and integration.
- Hydrocarbon production operations commonly involve numerous workflows that are repetitive in nature and which are traditionally undertaken manually or semi-manually by the various participants who spend significant portions of their time operating technical applications, finding and entering data, conducting analysis and passing data between participants for various steps such as validation and approval, in order to execute such workflows.
- any platform for automating workflows should include ways for non-expert users to interact with and execute complex workflows that were authored by the domain experts.
- Some common workflows may include, for example:
- the present invention meets the above needs and overcomes one or more deficiencies in the prior art by providing systems and methods for optimizing operational scenarios through a workflow, which i) automates various workflows and their routine execution between multiple participants; ii) provides a common operating environment for consistent execution of the workflows that is capable of substituting applications at various steps in any workflow; and iii) allows additional steps to be introduced into and incorporated within any workflow.
- the present invention includes a method for optimizing operational scenarios through a workflow, which comprises i) selecting an operating system platform, the operating system platform comprising a workflow application; ii) selecting a remote computing platform, the remote computing platform comprising a technical application for determining new operational scenarios, which is connected to the operating system platform by an application wrapper; and iii) selecting a system function to optimize the new operational scenarios, the system function being connected to the technical application by an application connector.
- the present invention includes a method for optimizing operational scenarios through a workflow, which comprises i) selecting an operating system platform, the operating system platform comprising a workflow application; ii) selecting a remote computing platform, the remote computing platform comprising a technical application for determining new operational scenarios, which is connected to the operating system platform by an application wrapper; and iii) selecting a system function to optimize a petrotechnical data model and test for new operational scenarios, the system function being connected to the technical application by an application connector.
- the present invention includes a method for optimizing operations scenarios through a workflow, which comprises i) selecting an operating system platform, the operating system platform comprising a workflow application; ii) selecting a remote computing platform, the remote computing platform comprising a technical application for determining new operational scenarios, which is connected to the operating system platform by an application connector; and iii) selecting a general workflow tool to optimize the new operational scenarios, the general workflow tool being connected to the technical application by an application connector.
- FIG. 1 illustrates one embodiment of a prior art system for implementing the present invention.
- FIG. 2A is a block diagram illustrating one embodiment of a computer system for implementing the present invention.
- FIG. 2B illustrates one embodiment of a system architecture for implementing the present invention.
- FIG. 3A illustrates a traditional routine workflow.
- FIG. 3B illustrates a traditional periodic workflow.
- FIG. 4A illustrates an automated routine workflow
- FIG. 4B illustrates an automated periodic workflow
- FIG. 5A illustrates an adaptive routine workflow
- FIG. 5B illustrates an adaptive periodic workflow
- FIG. 6 illustrates a simultaneous or concurrent synergistic workflow.
- FIG. 7 is a block diagram illustrating various workflows that may be performed within the framework of the present invention.
- FIG. 8 illustrates an exemplary deployment of the present invention.
- FIG. 9 illustrates one embodiment of a production management and optimization workflow according to the present invention.
- FIG. 10 illustrates one embodiment of a fracture stimulation design optimization workflow according to the present invention.
- FIG. 11 illustrates one embodiment of a production forecasting and planning workflow according to the present invention.
- FIG. 12 illustrates one embodiment of a gas lift allocation and optimization workflow according to the present invention.
- the present invention may be implemented through a computer-executable program of instructions, such as program modules, generally referred to as software applications or application programs executed by a computer.
- the software may include, for example, routines, programs, objects, components, and data structures that perform particular tasks or implement particular abstract data types.
- the software forms an interface to allow a computer to react according to a source of input.
- AssetConnectTM which is a commercial software application marketed by Landmark Graphics Corporation, may be used as an interface application to implement the present invention.
- the software may also cooperate with other code segments to initiate a variety of tasks in response to data received in conjunction with the source of the received data.
- the software may be stored onto any variety of memory media such as CD-ROM, magnetic disk, bubble memory and semiconductor memory (e.g., various types of RAM or ROM). Furthermore, the software and its results may be transmitted over a variety of carrier media such as optical fiber, metallic wire, free space and/or through any of a variety of networks such as the Internet.
- memory media such as CD-ROM, magnetic disk, bubble memory and semiconductor memory (e.g., various types of RAM or ROM).
- the software and its results may be transmitted over a variety of carrier media such as optical fiber, metallic wire, free space and/or through any of a variety of networks such as the Internet.
- the invention may be practiced with a variety of computer-system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable-consumer electronics, minicomputers, mainframe computers, and the like. Any number of computer-systems and computer networks are acceptable for use with the present invention.
- the invention may be practiced in distributed-computing environments where tasks are performed by remote-processing devices that are linked through a communications network.
- program modules may be located in both local and remote computer-storage media including memory storage devices.
- the present invention may therefore, be implemented in connection with various hardware, software or a combination thereof, in a computer system or other processing system.
- FIG. 2A a block diagram of a system for implementing the present invention on a computer is illustrated.
- the system includes a computing unit, sometimes referred to a computing system, which contains memory, application programs, a client interface, and a processing unit.
- the computing unit is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention.
- the memory primarily stores the application programs, which may also be described as program modules containing computer-executable instructions, executed by the computing unit for implementing the present invention described herein and illustrated in FIGS. 2 B and 4 - 12 .
- the memory therefore, includes one or more workflow modules, which enable the workflows illustrated in FIGS. 4-12 , and AssetConnectTM.
- the computing unit typically includes a variety of computer readable media.
- computer readable media may comprise computer storage media and communication media.
- the computing system memory may include computer storage media in the form of volatile and/or nonvolatile memory such as a read only memory (ROM) and random access memory (RAM).
- ROM read only memory
- RAM random access memory
- a basic input/output system (BIOS) containing the basic routines that help to transfer information between elements within the computing unit, such as during start-up, is typically stored in ROM.
- the RAM typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by the processing unit.
- the computing unit includes an operating system, application programs, other program modules, and program data.
- the components shown in the memory may also be included in other removable/nonremovable, volatile/nonvolatile computer storage media.
- a hard disk drive may read from or write to nonremovable, nonvolatile magnetic media
- a magnetic disk drive may read from or write to a removable, non-volatile magnetic disk
- an optical disk drive may read from or write to a removable, nonvolatile optical disk such as a CD ROM or other optical media.
- Other removable/non-removable, volatile/non-volatile computer storage media that can be used in the exemplary operating environment may include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like.
- the drives and their associated computer storage media discussed above provide storage of computer readable instructions, data structures, program modules and other data for the computing unit.
- a client may enter commands and information into the computing unit through the client interface, which may be input devices such as a keyboard and pointing device, commonly referred to as a mouse, trackball or touch pad.
- input devices may include a microphone, joystick, satellite dish, scanner, or the like.
- a monitor or other type of display device may be connected to the system bus via an interface, such as a video interface.
- computers may also include other peripheral output devices such as speakers and printer, which may be connected through an output peripheral interface.
- FIGS. 1 and 2A An exemplary system comprising such components is commonly referred to in the oil and gas industry as AssetConnectTM, which is illustrated in FIGS. 1 and 2A .
- FIG. 2B An exemplary system architecture for implementing the present invention is illustrated in FIG. 2B .
- FIG. 2B illustrates the interrelationship of the components in FIG. 1 , which may be used to perform the workflows illustrated in FIGS. 4-12 .
- PB-PN IT/Computing Platforms
- AB-AN various technical applications
- PB-PN IT/Computing Platforms
- AB-AN the various technical applications
- AB-AN may be interconnected for access to the required technical applications (AB-AN) by means of a Services Oriented Architecture, which permits a unified operating environment wherein the technical applications (AB-AN) can be remotely accessed for incorporation within a workflow.
- the various technical applications are able to be brought into the system from their remote IT platforms by means of Application Wrappers (WB-WN). Thereafter, within the unified operating environment, the technical applications (AB-AN) can be remotely operated within a workflow.
- the respective technical applications (AB-AN) provide their own functionality consistent with a step or steps in each workflow.
- the various technical applications (AA-AN) involved in a workflow are able to be connected by means of Application Connectors (CA-CN).
- the connectors (CA-CN) allow the workflow author to map to and to connect to attributes within the technical applications (AB-AN) and to map to and relate these to another technical application (AA-AN), effectively mapping inputs and outputs from one step of the workflow to another.
- the workflow logic can be determined to be consistent with the various steps, data and attribute flows within the workflow. In the simplest case, this enables automation of the workflow.
- the workflows can also be modified to introduce new-value-added steps by either connecting to additional System Functions (FA-FN) within the workflow orchestration application (AA) or, alternatively, by introducing additional technical applications (AB-AN) not routinely used within the traditional workflows.
- FA-FN System Functions
- AB-AN additional technical applications
- FIG. 3A and FIG. 3B a traditional routine workflow ( 3 A) and a traditional periodic workflow ( 3 B) are illustrated for production management and reservoir management, respectively.
- the traditional workflow is typically manually intensive and expert centric with delays experienced due to interdependencies across multiple participants—each using different applications appropriate to their area of expertise.
- Table 1 A definition of each workflow symbol utilized in the description of the following figures is provided in Table 1 below.
- participant A may interface with certain ‘system’ components.
- the participants may be represented by participant A being a field operative, participant B being a petroleum engineer and participant C being a reservoir engineer, for example. Additional participants may be preferred and/or necessary.
- the workflow steps are performed by the respective participants and at certain steps interfacing with system components and referenced applications.
- the referenced applications may therefore, include, for example, petrotechnical application A, which might be a nodal analysis application, and petrotechnical application B, which might be a reservoir simulation application.
- Analysis and reporting from use of application A might typically include representation of a calculated Inflow Production Ration (IPR curve), skin thickness, well performance plots, and the like.
- IPR curve Inflow Production Ration
- Analysis and reporting from use of application B might typically include representation of a calculated production profile, forecast, events detected (such as sand or water breakthrough), and the like. Operational scenarios resulting from such analysis might include adjusting choke settings, initiating well workovers or similar activities. Various other commercial applications may be similarly used in such workflows, which are well known in the art. The participants, system and applications described and illustrated in reference FIG. 3A and FIG. 3B may also be applied to the same workflow components illustrated in FIGS. 4A , 4 B, 5 A, 5 B and 6 .
- FIGS. 4-7 Exemplary workflows utilizing the system architecture, according to the method illustrated in FIG. 2B are illustrated in FIGS. 4-7 . Each figure either represents a routine workflow or one that is periodically performed. Changes to these workflows are denoted by shading the changed step(s). These workflows may be described as:
- an automated routine workflow ( 4 A) and an automated periodic workflow ( 4 B) are illustrated for production management and reservoir management, respectively.
- These workflows represent a typical (or actual) asset.
- Such automated workflows are characterized by the system performing many routine tasks previously performed by the participants, engaging the participants only when they are required, for example, to validate and outcome or to make or authorize a decision outcome.
- the shaded steps in the System column of FIG. 4A and FIG. 4B represent traditional workflow steps that are now automated within the system.
- the benefits are primarily in time saving and consistency, there is no significant change to the transformations effected by the steps of the workflows.
- the workflow logic is not substantially changed and core steps remain largely as normally executed; that is, no additional transformation occurs as a result of the automated workflow except that the participants experience is changed by means of automation.
- an adaptive routine workflow ( 5 A) and an adaptive periodic workflow ( 5 B) are illustrated for production management and reservoir management, respectively.
- Adaptive workflows are characterized by the system enabling additional tasks previously not performed by the participants, primarily due to time and technology constraints. The ability to both incorporate additional applications, functionality and computing resources readily, as well being able to automate time consuming tasks within the workflow allow for the workflows to make better use of all available resources.
- additional steps are enabled that were not previously performed by the participants or the system in the traditional workflows ( FIG. 3A and FIG.
- the shaded step in the System column of FIG. 5A represents a change from the corresponding step in FIG. 4A (step 4 ).
- the benefits are in the value added by additional steps introduced to the workflow.
- There are significant changes to the transformations effected by the additional steps of the workflows which include novel changes to the workflow logic (e.g. from a linear workflow to a non-linear flow or the introduction of additional iterations that add value), and novel additional activities introduced to the workflow (such as novel analysis and changed use of i) traditional data, ii) novel data derived from novel activities or iii) aggregate data sets) not normally undertaken by the traditional workflow.
- the super workflows created by integrating multiple traditional workflows may encompass the key facets of either automated and/or adaptive workflows, and may introduce further novel transformative steps as illustrated by the shading of various steps.
- FIG. 7 a block diagram illustrates various workflows traditionally associated with both reservoir and production management activities that may be performed within the framework of the present invention in either automated, adaptive or synergistic workflows.
- FIG. 8 an exemplary deployment of the present invention is illustrated. Considerations for deployment of such automated or transformed workflows must include access for a wider audience of users beyond the technical workflow author.
- a typical user of an automated workflow may not be intimately familiar with the individual applications or models, which make up the workflow.
- a central library of workflows may be maintained and distributed to expert and non-expert users through either a desktop client or a web-based interface where users can both initiate workflows and view progress and results.
- the centralized library is a secure computing environment where individual workflows and their associated applications and models can be maintained and versioned accordingly to maintain their integrity.
- FIG. 7 Several embodiments of the workflows illustrated in FIG. 7 are addressed in reference to FIGS. 9-12 and may be performed within the workflow framework of an automated adaptive and/or synergistic workflow according to FIGS. 4-6 .
- FIG. 9 illustrates such a workflow.
- EDMTM assets production database
- EDMTM is a commercial database application marketed by Landmark Graphics Corporation.
- ProsperTM is a commercial software application marketed by Petroleum Experts. This theoretical rate is stored in the production database and can then be visualized against the measured flow on a regular basis. Wells which deviate significantly from its theoretical performance can be flagged to the production engineer for immediate attention.
- the invention may be applied to a fracture design workflow.
- Fracturing is a technique applied to petroleum wells to establish or improve the flow of petroleum into a well completion for an extended period of time.
- the fracture treatment has a limited lifespan and is not inexpensive. Applying a fracture treatment to a well may well cost between Two Hundred Fifty Thousand Dollars ($250,000.00) and Five Hundred Thousand Dollars ($500,000.00), if not more, per treatment.
- the expected life of a treatment is between two and five years.
- the effectiveness of a fracture is dependent upon the characteristics of the reservoir rock and the design of the fracture. Often there is considerable uncertainty of the reservoir rock characteristics. In some cases, the uncertainty of reservoir rock may be mitigated by the fracture design.
- the fracture design workflow has two basic functions: fracture design evaluation and fracture design optimization.
- fracture design evaluation is accomplished by three applications.
- the first application permits a user to review a well log record and to make an evaluation of the reservoir characteristics for the section or sections of the wellbore to be fractured. The results of this evaluation is shared with the second and third applications.
- This first application may be performed using PrizmTM, which is a commercial software application marketed by Landmark Graphics Corporation, although other applications are available with similar capabilities.
- the second application permits a user to adjust the fracture design parameters and to estimate the expected fracture dimensions, namely fracture half length, fracture height, and fracture width.
- This second application may be performed using FracPro®, which is a commercial software application marketed by Pinnacle Technologies, although other applications are available with similar capabilities.
- a third application which uses the reservoir characteristics and fracture dimensions for a specific treatment design to make an estimate of the resultant well completion cumulative production over the expected life of the fracture treatment.
- This third application may be performed in an established tool known as Predict KTM, which is a commercial software application marketed by Core Lab, although other applications are available with similar capabilities. After the workflow is developed using these three applications, the scope of the workflow may be widened to use other applications in a similar manner.
- Fracture design optimization may use the basic FDE process to evaluate a set of fracture designs to determine which design gives the best cumulative production. Further, each design in the set may be evaluated over a range of reservoir uncertainty so that the fracture designs may also be optimized with regard to reservoir uncertainty.
- This workflow automates all aspects of the design execute evaluate and learn (DEEL) loop for well stimulation and completion activities for a tight gas field.
- DEEL evaluate and learn
- the digital completion optimization system creates a common platform for all activities.
- the design workflow incorporates well log analysis from a program such as Prizm® with geology stress analysis and production prediction (e.g. SWIFT®, which is a commercial software application marketed by Halliburton Energy Services Inc.) and a fracture design program (e.g.
- StimplanTM which is a commercial software application marketed by NSI Technologies.
- the design workflow is explained in detail in the Frac Stimulation Design Optimization above.
- the execution workflow monitors the fracture job and automatically history matches the fracture design and well production predictions.
- the evaluate loop utilizes artificial intelligence algorithms such as neural networks and support vectors to mine the data generated from all of the design and execution workflows on all jobs from multiple databases.
- the analysis from the data mining workflow is used in an optimization system to update design parameters used in the design and execute workflows.
- FIG. 11 illustrates an exemplary embodiment of this workflow.
- Gas lift is a popular method for enhancing production in heavier oil wells.
- increasing the performance constraints of the downstream facilities are limiting the total amount of gas lift available.
- Making the right decisions on how much gas lift to send to which well is a complex process involving well performance models, flowline hydraulics and facility process performance.
- An example of a gas lift allocation and optimization workflow is illustrated in FIG. 12 .
- This invention therefore, provides a flexible framework within which multiple and disparate workflows may be performed as an automated, adaptive or synergistic workflow using a common platform and domain.
- Each type of workflow adds value across a diverse range of workflows.
- lost time spent finding the data and operating the technical applications that underpin core workflows, which has been cited by some operators as consuming up to 75% engineering time, is reduced.
- the present invention therefore, enables:
Abstract
Description
- The priority of U.S. Provisional Patent Application No. 60/987,066, filed on Nov. 10, 2007, is hereby claimed, and the specification thereof is incorporated herein by reference.
- Not applicable.
- The present invention generally relates to systems and methods for implementing complex and disparate workflows and, more particularly, a flexible framework for workflow automation, adaptation and integration.
- Hydrocarbon production operations commonly involve numerous workflows that are repetitive in nature and which are traditionally undertaken manually or semi-manually by the various participants who spend significant portions of their time operating technical applications, finding and entering data, conducting analysis and passing data between participants for various steps such as validation and approval, in order to execute such workflows.
- Studies have shown, for example that about 70% of an engineers time is spent gathering, formatting, and translating data for use in these different applications. For standard production activities, i.e., workflows, this time can be drastically reduced by creating an automated system to execute the prescribed workflow. The automated workflow not only reduces the engineers valuable time doing these repetitive tasks, but also ensures consistency in methods, reduces the likelihood of input errors, and creates a repository for “best practices” that can be maintained long term as personnel (and their knowledge) is moved into and out of the production asset.
- Additionally, it is common experience that participants in many workflows have different preferences for, and levels of, expertise on numerous applications, which they utilize at respective steps in common workflows. This diversity makes standardization and consistency difficult to achieve.
- Furthermore, due to time demands placed by the various workflows, potentially valuable additional analysis options are not routinely undertaken nor are aggregate data sets routinely reviewed in order to learn from the results.
- In other industries, and elsewhere in the exploration and production field, business process management systems and certain specific technical application based workflows are automated and orchestrated using different methods and systems from those described by the present invention. Due to the diversity of technology, applications and workflows however, the challenge of workflow orchestration has largely been unresolved.
- For many years automated workflows have been a part of the design and production cycles in other industries like Aerospace, Automotive, and Industrial Manufacturing. These industries have been tying together applications and data sources along with using stochastic analysis methods and optimization to improve their overall productivity.
- Today's oil and gas operators face daunting challenges. With rising global demand, declining production, growing data volumes, dwindling resources, mounting regulatory and environmental pressures, exploration and production companies must dramatically improve the management of their hydrocarbon assets. The automation of common workflows can help mitigate these challenges by providing a common, best-practice method of execution that can be sustained and measured.
- Execution of these automated workflows also must be examined. As production operations become more complex, their associated workflows will also become more complex. It can not be assumed that the end-user of an automated workflow is an “expert” user and has the knowledge and experience to operate all the needed software application interfaces. Ideally, any platform for automating workflows should include ways for non-expert users to interact with and execute complex workflows that were authored by the domain experts.
- Currently, oil and gas production workflow automation is typically done through custom integration of disparate systems often requiring engineers to coordinate data flows between a disparate number of applications. Some common workflows may include, for example:
- 1. Production management and optimization;
- 2. Fracture stimulation design optimization;
- 3. Production forecasting and planning; and
- 4. Gas-lift allocation and optimization.
- The custom integration of multiple applications, however, has many deficiencies and would be better replaced by a more standardized framework of integration.
- The advantages of workflow automation and integration of various applications are generally described in U.S. Pat. Nos. 6,266,619, 6,356,844, 6,853,921, and 7,079,952, which are assigned to Halliburton Energy Services, Inc. and incorporated herein by reference. These patents generally deal with a field wide reservoir management system. The system includes a suite of tools (computer programs) that seamlessly interface with each other to generate a field wide production and injection forecast. The system produces real time control of downhole production and injection control devices such as chokes, valves and other flow control devices and real time control of surface production and injection control devices. The system, however, does not address a flexible framework that encompasses automated workflows, adaptive workflows and synergistic workflows as defined by the present invention.
- Therefore, there is a need for a flexible workflow framework that 1) automates various workflows and their routine execution between multiple participants; 2) provides a common operating environment for consistent execution of the workflows, which is capable of substituting applications at various steps in any workflow; and 3) allows additional steps to be introduced into and incorporated within any workflow.
- The workflow framework must therefore, address the following:
- 1. Moving location of boundary conditions, inputs and output extraction within multi-disciplinary and multi-vendor environments;
- 2. Intelligent generation and execution of up to thousands of multi-disciplinary simulations; and
- 3. Convenient storage/retrieval and interpretation of the results.
- The present invention meets the above needs and overcomes one or more deficiencies in the prior art by providing systems and methods for optimizing operational scenarios through a workflow, which i) automates various workflows and their routine execution between multiple participants; ii) provides a common operating environment for consistent execution of the workflows that is capable of substituting applications at various steps in any workflow; and iii) allows additional steps to be introduced into and incorporated within any workflow.
- In one embodiment, the present invention includes a method for optimizing operational scenarios through a workflow, which comprises i) selecting an operating system platform, the operating system platform comprising a workflow application; ii) selecting a remote computing platform, the remote computing platform comprising a technical application for determining new operational scenarios, which is connected to the operating system platform by an application wrapper; and iii) selecting a system function to optimize the new operational scenarios, the system function being connected to the technical application by an application connector.
- In another, the present invention includes a method for optimizing operational scenarios through a workflow, which comprises i) selecting an operating system platform, the operating system platform comprising a workflow application; ii) selecting a remote computing platform, the remote computing platform comprising a technical application for determining new operational scenarios, which is connected to the operating system platform by an application wrapper; and iii) selecting a system function to optimize a petrotechnical data model and test for new operational scenarios, the system function being connected to the technical application by an application connector.
- In yet another embodiment, the present invention includes a method for optimizing operations scenarios through a workflow, which comprises i) selecting an operating system platform, the operating system platform comprising a workflow application; ii) selecting a remote computing platform, the remote computing platform comprising a technical application for determining new operational scenarios, which is connected to the operating system platform by an application connector; and iii) selecting a general workflow tool to optimize the new operational scenarios, the general workflow tool being connected to the technical application by an application connector.
- Additional aspects, advantages and embodiments of the invention will become apparent to those skilled in the art from the following description of the various embodiments and related drawings.
- The present invention is described below with references to the accompanying drawings in which like elements are referenced with like reference numerals, and in which:
-
FIG. 1 illustrates one embodiment of a prior art system for implementing the present invention. -
FIG. 2A is a block diagram illustrating one embodiment of a computer system for implementing the present invention. -
FIG. 2B illustrates one embodiment of a system architecture for implementing the present invention. -
FIG. 3A illustrates a traditional routine workflow. -
FIG. 3B illustrates a traditional periodic workflow. -
FIG. 4A illustrates an automated routine workflow. -
FIG. 4B illustrates an automated periodic workflow. -
FIG. 5A illustrates an adaptive routine workflow. -
FIG. 5B illustrates an adaptive periodic workflow. -
FIG. 6 illustrates a simultaneous or concurrent synergistic workflow. -
FIG. 7 is a block diagram illustrating various workflows that may be performed within the framework of the present invention. -
FIG. 8 illustrates an exemplary deployment of the present invention. -
FIG. 9 illustrates one embodiment of a production management and optimization workflow according to the present invention. -
FIG. 10 illustrates one embodiment of a fracture stimulation design optimization workflow according to the present invention. -
FIG. 11 illustrates one embodiment of a production forecasting and planning workflow according to the present invention. -
FIG. 12 illustrates one embodiment of a gas lift allocation and optimization workflow according to the present invention. - The subject matter of the present invention is described with specificity, however, the description itself is not intended to limit the scope of the invention. The subject matter thus, might also be embodied in other ways, to include different steps or combinations of steps similar to the ones described herein, in conjunction with other present or future technologies. Moreover, although the term “step” may be used herein to describe different elements of methods employed, the term should not be interpreted as implying any particular order among or between various steps herein disclosed unless otherwise expressly limited by the description to a particular order.
- The present invention may be implemented through a computer-executable program of instructions, such as program modules, generally referred to as software applications or application programs executed by a computer. The software may include, for example, routines, programs, objects, components, and data structures that perform particular tasks or implement particular abstract data types. The software forms an interface to allow a computer to react according to a source of input. AssetConnect™, which is a commercial software application marketed by Landmark Graphics Corporation, may be used as an interface application to implement the present invention. The software may also cooperate with other code segments to initiate a variety of tasks in response to data received in conjunction with the source of the received data. The software may be stored onto any variety of memory media such as CD-ROM, magnetic disk, bubble memory and semiconductor memory (e.g., various types of RAM or ROM). Furthermore, the software and its results may be transmitted over a variety of carrier media such as optical fiber, metallic wire, free space and/or through any of a variety of networks such as the Internet.
- Moreover, those skilled in the art will appreciate that the invention may be practiced with a variety of computer-system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable-consumer electronics, minicomputers, mainframe computers, and the like. Any number of computer-systems and computer networks are acceptable for use with the present invention. The invention may be practiced in distributed-computing environments where tasks are performed by remote-processing devices that are linked through a communications network. In a distributed-computing environment, program modules may be located in both local and remote computer-storage media including memory storage devices. The present invention may therefore, be implemented in connection with various hardware, software or a combination thereof, in a computer system or other processing system.
- Referring now to
FIG. 2A , a block diagram of a system for implementing the present invention on a computer is illustrated. The system includes a computing unit, sometimes referred to a computing system, which contains memory, application programs, a client interface, and a processing unit. The computing unit is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention. - The memory primarily stores the application programs, which may also be described as program modules containing computer-executable instructions, executed by the computing unit for implementing the present invention described herein and illustrated in FIGS. 2B and 4-12. The memory therefore, includes one or more workflow modules, which enable the workflows illustrated in
FIGS. 4-12 , and AssetConnect™. - Although the computing unit is shown as having a generalized memory, the computing unit typically includes a variety of computer readable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. The computing system memory may include computer storage media in the form of volatile and/or nonvolatile memory such as a read only memory (ROM) and random access memory (RAM). A basic input/output system (BIOS), containing the basic routines that help to transfer information between elements within the computing unit, such as during start-up, is typically stored in ROM. The RAM typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by the processing unit. By way of example, and not limitation, the computing unit includes an operating system, application programs, other program modules, and program data.
- The components shown in the memory may also be included in other removable/nonremovable, volatile/nonvolatile computer storage media. For example only, a hard disk drive may read from or write to nonremovable, nonvolatile magnetic media, a magnetic disk drive may read from or write to a removable, non-volatile magnetic disk, and an optical disk drive may read from or write to a removable, nonvolatile optical disk such as a CD ROM or other optical media. Other removable/non-removable, volatile/non-volatile computer storage media that can be used in the exemplary operating environment may include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The drives and their associated computer storage media discussed above provide storage of computer readable instructions, data structures, program modules and other data for the computing unit.
- A client may enter commands and information into the computing unit through the client interface, which may be input devices such as a keyboard and pointing device, commonly referred to as a mouse, trackball or touch pad. Input devices may include a microphone, joystick, satellite dish, scanner, or the like.
- These and other input devices are often connected to the processing unit through the client interface that is coupled to a system bus, but may be connected by other interface and bus structures, such as a parallel port or a universal serial bus (USB). A monitor or other type of display device may be connected to the system bus via an interface, such as a video interface. In addition to the monitor, computers may also include other peripheral output devices such as speakers and printer, which may be connected through an output peripheral interface.
- Certain system components, which are well known in the art and may be used for implementing the present invention, include:
- 1. IT/Computing Platforms: PA-PN, where PA is the systems operating environment and PB-PN are all other computing environments common to oil and gas production.
- 2. Applications: AA-AN, where application AA is the workflow orchestration application and AB-AN are all other technical applications common to oil and gas production.
- 3. Application Wrappers: WA-WN, the workflow orchestration application includes a software development kit for development of application wrappers for other applications. Alternatively, Application Wrappers WA-WN and System Functions FA-FN need not both be present. Instead, Application Connectors and general workflow tools (i.e., calculator, data transfer, OS command, etc.) may be used.
- 4. System Functions FA-FN, the system incorporates numerous functions enabling additional analytics and steps to be incorporated within a given workflow (e.g. Monte-Carlo simulation, optimization, etc).
- An exemplary system comprising such components is commonly referred to in the oil and gas industry as AssetConnect™, which is illustrated in
FIGS. 1 and 2A . - Although many other internal components of the computing unit are not shown, those of ordinary skill in the art will appreciate that such components and their interconnection are well known.
- An exemplary system architecture for implementing the present invention is illustrated in
FIG. 2B .FIG. 2B illustrates the interrelationship of the components inFIG. 1 , which may be used to perform the workflows illustrated inFIGS. 4-12 . - Referring now to
FIG. 2B , the various IT/Computing Platforms (PB-PN), for example, Linux, Windows, etc., which may house the various technical applications (AB-AN), may be interconnected for access to the required technical applications (AB-AN) by means of a Services Oriented Architecture, which permits a unified operating environment wherein the technical applications (AB-AN) can be remotely accessed for incorporation within a workflow. - The various technical applications (AB-AN) are able to be brought into the system from their remote IT platforms by means of Application Wrappers (WB-WN). Thereafter, within the unified operating environment, the technical applications (AB-AN) can be remotely operated within a workflow. The respective technical applications (AB-AN) provide their own functionality consistent with a step or steps in each workflow.
- The various technical applications (AA-AN) involved in a workflow are able to be connected by means of Application Connectors (CA-CN). The connectors (CA-CN) allow the workflow author to map to and to connect to attributes within the technical applications (AB-AN) and to map to and relate these to another technical application (AA-AN), effectively mapping inputs and outputs from one step of the workflow to another. In this manner, the workflow logic can be determined to be consistent with the various steps, data and attribute flows within the workflow. In the simplest case, this enables automation of the workflow.
- The workflows can also be modified to introduce new-value-added steps by either connecting to additional System Functions (FA-FN) within the workflow orchestration application (AA) or, alternatively, by introducing additional technical applications (AB-AN) not routinely used within the traditional workflows.
- Using unique combinations of the system component capabilities in the manner illustrated in
FIG. 2B , it is possible to enable automation of the traditional workflow and also to modify the traditional workflow logic to incorporate various combinations of the above capabilities—i.e., in effect enabling novel workflows that are significantly additive to the traditional workflow. The present invention therefore, enables the flow of real time data that can be used for routine (continuous) workflows. - Referring now to
FIG. 3A andFIG. 3B , a traditional routine workflow (3A) and a traditional periodic workflow (3B) are illustrated for production management and reservoir management, respectively. The traditional workflow is typically manually intensive and expert centric with delays experienced due to interdependencies across multiple participants—each using different applications appropriate to their area of expertise. A definition of each workflow symbol utilized in the description of the following figures is provided in Table 1 below. - In
FIG. 3A andFIG. 3B , participants A, B and C may interface with certain ‘system’ components. The participants may be represented by participant A being a field operative, participant B being a petroleum engineer and participant C being a reservoir engineer, for example. Additional participants may be preferred and/or necessary. The workflow steps are performed by the respective participants and at certain steps interfacing with system components and referenced applications. The referenced applications may therefore, include, for example, petrotechnical application A, which might be a nodal analysis application, and petrotechnical application B, which might be a reservoir simulation application. Analysis and reporting from use of application A might typically include representation of a calculated Inflow Production Ration (IPR curve), skin thickness, well performance plots, and the like. Analysis and reporting from use of application B might typically include representation of a calculated production profile, forecast, events detected (such as sand or water breakthrough), and the like. Operational scenarios resulting from such analysis might include adjusting choke settings, initiating well workovers or similar activities. Various other commercial applications may be similarly used in such workflows, which are well known in the art. The participants, system and applications described and illustrated in referenceFIG. 3A andFIG. 3B may also be applied to the same workflow components illustrated inFIGS. 4A , 4B, 5A, 5B and 6. - Exemplary workflows utilizing the system architecture, according to the method illustrated in
FIG. 2B are illustrated inFIGS. 4-7 . Each figure either represents a routine workflow or one that is periodically performed. Changes to these workflows are denoted by shading the changed step(s). These workflows may be described as: - 1) Automated workflows, whereby the traditional workflow is automated to remove significant demands on the participants in order to operate the workflow;
- 2) Adaptive workflows, whereby the traditional workflow is significantly changed by means of introduction of additional steps or functionality that effect additional transformation within the workflow; and
- 3) Synergistic workflows, whereby multiple traditional workflows are integrated to create a ‘super’ workflow that spans and orchestrates the multiple workflows to effect novel transformations that would not normally be otherwise achieved by the individual traditional workflows.
- Referring now to
FIG. 4A andFIG. 4B , an automated routine workflow (4A) and an automated periodic workflow (4B) are illustrated for production management and reservoir management, respectively. These workflows represent a typical (or actual) asset. Such automated workflows are characterized by the system performing many routine tasks previously performed by the participants, engaging the participants only when they are required, for example, to validate and outcome or to make or authorize a decision outcome. As illustrated by the comparison ofFIG. 3A toFIG. 4A andFIG. 3B toFIG. 4B , the shaded steps in the System column ofFIG. 4A andFIG. 4B represent traditional workflow steps that are now automated within the system. The benefits are primarily in time saving and consistency, there is no significant change to the transformations effected by the steps of the workflows. The workflow logic is not substantially changed and core steps remain largely as normally executed; that is, no additional transformation occurs as a result of the automated workflow except that the participants experience is changed by means of automation. This could be as simple as automation of operation of a singe application considered a workflow or, alternatively, could involve multiple applications and steps considered to be a workflow. - Referring now to
FIG. 5A andFIG. 5B , an adaptive routine workflow (5A) and an adaptive periodic workflow (5B) are illustrated for production management and reservoir management, respectively. Adaptive workflows are characterized by the system enabling additional tasks previously not performed by the participants, primarily due to time and technology constraints. The ability to both incorporate additional applications, functionality and computing resources readily, as well being able to automate time consuming tasks within the workflow allow for the workflows to make better use of all available resources. As illustrated by the shaded steps inFIG. 5A (steps 4 a and 8 a) andFIG. 5B (steps 3 a and 8 a), additional steps are enabled that were not previously performed by the participants or the system in the traditional workflows (FIG. 3A andFIG. 3B ) and the automated workflows (FIG. 4A andFIG. 4B ). The shaded step in the System column ofFIG. 5A (step 4) represents a change from the corresponding step inFIG. 4A (step 4). The benefits are in the value added by additional steps introduced to the workflow. There are significant changes to the transformations effected by the additional steps of the workflows, which include novel changes to the workflow logic (e.g. from a linear workflow to a non-linear flow or the introduction of additional iterations that add value), and novel additional activities introduced to the workflow (such as novel analysis and changed use of i) traditional data, ii) novel data derived from novel activities or iii) aggregate data sets) not normally undertaken by the traditional workflow. - Referring now to
FIG. 6 , a simultaneous or concurrent synergistic workflow is illustrated. The super workflows created by integrating multiple traditional workflows may encompass the key facets of either automated and/or adaptive workflows, and may introduce further novel transformative steps as illustrated by the shading of various steps. - Referring now to
FIG. 7 , a block diagram illustrates various workflows traditionally associated with both reservoir and production management activities that may be performed within the framework of the present invention in either automated, adaptive or synergistic workflows. - Referring now to
FIG. 8 , an exemplary deployment of the present invention is illustrated. Considerations for deployment of such automated or transformed workflows must include access for a wider audience of users beyond the technical workflow author. A typical user of an automated workflow may not be intimately familiar with the individual applications or models, which make up the workflow. A central library of workflows may be maintained and distributed to expert and non-expert users through either a desktop client or a web-based interface where users can both initiate workflows and view progress and results. The centralized library is a secure computing environment where individual workflows and their associated applications and models can be maintained and versioned accordingly to maintain their integrity. - Several embodiments of the workflows illustrated in
FIG. 7 are addressed in reference toFIGS. 9-12 and may be performed within the workflow framework of an automated adaptive and/or synergistic workflow according toFIGS. 4-6 . - Production engineers are increasingly asked to optimize the performance of larger and more complex assets. Their well counts are getting higher and the amount of data they need to analyze is ever expanding. By automating the well performance data acquisition and analysis, the production engineer can better manage his field by exception and focus his attention on the areas with the most potential value.
FIG. 9 illustrates such a workflow. - In this workflow, field measured well head pressures and flows are regularly collected by the assets production database (e.g. EDM™). EDM™ is a commercial database application marketed by Landmark Graphics Corporation. On daily intervals, the automated workflow framework collects well pressures and current reservoir pressure(s) from the production database(s). The automated workflow uses a rigorous well model (e.g. Prosper™) to estimate the theoretical flow of each well. Prosper™ is a commercial software application marketed by Petroleum Experts. This theoretical rate is stored in the production database and can then be visualized against the measured flow on a regular basis. Wells which deviate significantly from its theoretical performance can be flagged to the production engineer for immediate attention.
- Billions of dollars are spent annually on fracture stimulation operations. It is critical that these expensive operations be done right and on-time. Accurate and optimal designs are key to ensuring a successful facture operation. However, a successful design includes several technical components such as rock mechanics and properties, fluid properties and scheduling, frac conditions and placement, and economic conditions. Software applications exist for all of these to help engineers. One example of how these applications may be integrated in a workflow is illustrated in
FIG. 10 . - In a preferred embodiment, the invention may be applied to a fracture design workflow. Fracturing is a technique applied to petroleum wells to establish or improve the flow of petroleum into a well completion for an extended period of time. The fracture treatment has a limited lifespan and is not inexpensive. Applying a fracture treatment to a well may well cost between Two Hundred Fifty Thousand Dollars ($250,000.00) and Five Hundred Thousand Dollars ($500,000.00), if not more, per treatment. The expected life of a treatment is between two and five years. As can be appreciated, the effectiveness of a fracture is dependent upon the characteristics of the reservoir rock and the design of the fracture. Often there is considerable uncertainty of the reservoir rock characteristics. In some cases, the uncertainty of reservoir rock may be mitigated by the fracture design. Thus the fracture design workflow has two basic functions: fracture design evaluation and fracture design optimization.
- In a preferred embodiment, fracture design evaluation (FDE) is accomplished by three applications. The first application permits a user to review a well log record and to make an evaluation of the reservoir characteristics for the section or sections of the wellbore to be fractured. The results of this evaluation is shared with the second and third applications. This first application may be performed using Prizm™, which is a commercial software application marketed by Landmark Graphics Corporation, although other applications are available with similar capabilities. The second application permits a user to adjust the fracture design parameters and to estimate the expected fracture dimensions, namely fracture half length, fracture height, and fracture width. This second application may be performed using FracPro®, which is a commercial software application marketed by Pinnacle Technologies, although other applications are available with similar capabilities. Finally, a third application is used which uses the reservoir characteristics and fracture dimensions for a specific treatment design to make an estimate of the resultant well completion cumulative production over the expected life of the fracture treatment. This third application may be performed in an established tool known as Predict K™, which is a commercial software application marketed by Core Lab, although other applications are available with similar capabilities. After the workflow is developed using these three applications, the scope of the workflow may be widened to use other applications in a similar manner.
- Fracture design optimization may use the basic FDE process to evaluate a set of fracture designs to determine which design gives the best cumulative production. Further, each design in the set may be evaluated over a range of reservoir uncertainty so that the fracture designs may also be optimized with regard to reservoir uncertainty.
- This workflow automates all aspects of the design execute evaluate and learn (DEEL) loop for well stimulation and completion activities for a tight gas field. In order to maximize production and minimize completion costs many different disciplines and activities are needed; geology, geophysics, stimulation, and production people have to work collaboratively. It is common that each of these disciplines work singularly and serially passing work product between one another. Furthermore the teams cannot effectively review past results and easily incorporate any lessons. The digital completion optimization system creates a common platform for all activities. The design workflow incorporates well log analysis from a program such as Prizm® with geology stress analysis and production prediction (e.g. SWIFT®, which is a commercial software application marketed by Halliburton Energy Services Inc.) and a fracture design program (e.g. Stimplan™, which is a commercial software application marketed by NSI Technologies). The design workflow is explained in detail in the Frac Stimulation Design Optimization above. The execution workflow monitors the fracture job and automatically history matches the fracture design and well production predictions. The evaluate loop utilizes artificial intelligence algorithms such as neural networks and support vectors to mine the data generated from all of the design and execution workflows on all jobs from multiple databases. The analysis from the data mining workflow is used in an optimization system to update design parameters used in the design and execute workflows.
FIG. 11 illustrates an exemplary embodiment of this workflow. - Gas lift is a popular method for enhancing production in heavier oil wells. However, increasingly the performance constraints of the downstream facilities are limiting the total amount of gas lift available. Making the right decisions on how much gas lift to send to which well is a complex process involving well performance models, flowline hydraulics and facility process performance. An example of a gas lift allocation and optimization workflow is illustrated in
FIG. 12 . - In this workflow, individual well gas lift injection rates must be optimized based on overall production benefits and the availability of lift gas. On a regular basis, perhaps nightly, production data is captured and used as input for well, gathering network and facility models. Individual well gas lift rates can then be allocated across all the wells and optimized for maximum oil production while maintaining any applicable surface constraints.
- This invention therefore, provides a flexible framework within which multiple and disparate workflows may be performed as an automated, adaptive or synergistic workflow using a common platform and domain. Each type of workflow adds value across a diverse range of workflows. Thus, lost time spent finding the data and operating the technical applications that underpin core workflows, which has been cited by some operators as consuming up to 75% engineering time, is reduced. The present invention therefore, enables:
- 1. Collaborative orchestration of diverse technical oriented workflows common to upstream oil and gas production within a common computing environment;
- 2. Automation of multi-step workflows involving the use of diverse technical applications;
- 3. Transformation of automated workflows through the introduction of novel, value-added steps, not normally practical within the upstream oil and gas operations environment;
- 4. Interchangeability of specific technical applications within common workflows in order to accommodate a diversity of preferred applications experienced in the upstream oil and gas production community;
- 5, Wide enterprise access to the automated and transformed workflows through a centrally managed “library” and desktop or web based GUI; and
- 6. Integrity of the workflow by centrally managing the versioning of individual workflows and their constituent application components.
- While the present invention has been described in connection with presently preferred embodiments, it will be understood by those skilled in the art that it is not intended to limit the invention to those embodiments. It is therefore, contemplated that various alternative embodiments and modifications may be made to the disclosed embodiments without departing from the spirit and scope of the invention defined by the appended claims and equivalents thereof.
Claims (20)
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US12/266,766 US20090125362A1 (en) | 2007-11-10 | 2008-11-07 | Systems and Methods For Workflow Automation, Adaptation and Integration |
US12/842,772 US9128693B2 (en) | 2007-11-10 | 2010-07-23 | Systems and methods for workflow automation, adaptation and integration |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US98706607P | 2007-11-10 | 2007-11-10 | |
US12/266,766 US20090125362A1 (en) | 2007-11-10 | 2008-11-07 | Systems and Methods For Workflow Automation, Adaptation and Integration |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/842,772 Continuation US9128693B2 (en) | 2007-11-10 | 2010-07-23 | Systems and methods for workflow automation, adaptation and integration |
Publications (1)
Publication Number | Publication Date |
---|---|
US20090125362A1 true US20090125362A1 (en) | 2009-05-14 |
Family
ID=40624625
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/266,766 Abandoned US20090125362A1 (en) | 2007-11-10 | 2008-11-07 | Systems and Methods For Workflow Automation, Adaptation and Integration |
US12/842,772 Active US9128693B2 (en) | 2007-11-10 | 2010-07-23 | Systems and methods for workflow automation, adaptation and integration |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/842,772 Active US9128693B2 (en) | 2007-11-10 | 2010-07-23 | Systems and methods for workflow automation, adaptation and integration |
Country Status (8)
Country | Link |
---|---|
US (2) | US20090125362A1 (en) |
EP (2) | EP2605191A3 (en) |
CN (1) | CN102007504A (en) |
AU (1) | AU2008323932B2 (en) |
BR (1) | BRPI0817402A2 (en) |
CA (1) | CA2705319C (en) |
MX (1) | MX2010005116A (en) |
WO (1) | WO2009061903A2 (en) |
Cited By (70)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100005111A1 (en) * | 2008-04-04 | 2010-01-07 | Landmark Graphics Corporation, A Halliburton Company | Systems and Methods for Correlating Meta-Data Model Representations and Asset-Logic Model Representations |
US20100192077A1 (en) * | 2009-01-26 | 2010-07-29 | Raytheon Company | Parent/Child Control System for a Workflow Automation Tool |
US20110022435A1 (en) * | 2007-11-10 | 2011-01-27 | Landmark Graphics Corporation, A Halliburton Company | Systems and Methods for Workflow Automation, Adaptation and Integration |
US20110093864A1 (en) * | 2009-10-21 | 2011-04-21 | Wood Stephen B | Integrated Workflow Builder |
US20110153300A1 (en) * | 2008-11-06 | 2011-06-23 | Holl James E | System and Method For Planning A Drilling Operation |
US20110172976A1 (en) * | 2008-10-01 | 2011-07-14 | Budiman Benny S | Robust Well Trajectory Planning |
US20110218775A1 (en) * | 2010-03-08 | 2011-09-08 | Czernuszenko Marek K | System and Method For Providing Data Corresponding To Physical Objects |
US20120166967A1 (en) * | 2010-12-28 | 2012-06-28 | Schlumberger Technology Corporation | Methods, systems, apparatuses, and computer-readable mediums for provisioning petrotechnical workflows in a cloud computing environment |
US20120317209A1 (en) * | 2011-06-13 | 2012-12-13 | Jason Rex Briggs | System and method for managing and implementing procedures and practices |
CN103392054A (en) * | 2011-02-23 | 2013-11-13 | 兰德马克绘图国际公司 | Method and systems of determining viable hydraulic fracture scenarios |
US8731873B2 (en) | 2010-04-26 | 2014-05-20 | Exxonmobil Upstream Research Company | System and method for providing data corresponding to physical objects |
US8731887B2 (en) | 2010-04-12 | 2014-05-20 | Exxonmobile Upstream Research Company | System and method for obtaining a model of data describing a physical structure |
US8731875B2 (en) | 2010-08-13 | 2014-05-20 | Exxonmobil Upstream Research Company | System and method for providing data corresponding to physical objects |
US8727017B2 (en) | 2010-04-22 | 2014-05-20 | Exxonmobil Upstream Research Company | System and method for obtaining data on an unstructured grid |
CN103824162A (en) * | 2014-02-28 | 2014-05-28 | 北京航空航天大学 | Reliability and performance integrated flexible workflow implementing method based on instruction chain |
US20140214476A1 (en) * | 2013-01-31 | 2014-07-31 | Halliburton Energy Services, Inc. | Data initialization for a subterranean operation |
US8884964B2 (en) | 2008-04-22 | 2014-11-11 | Exxonmobil Upstream Research Company | Functional-based knowledge analysis in a 2D and 3D visual environment |
US20140343982A1 (en) * | 2013-05-14 | 2014-11-20 | Landmark Graphics Corporation | Methods and systems related to workflow mentoring |
US8931580B2 (en) | 2010-02-03 | 2015-01-13 | Exxonmobil Upstream Research Company | Method for using dynamic target region for well path/drill center optimization |
US9026417B2 (en) | 2007-12-13 | 2015-05-05 | Exxonmobil Upstream Research Company | Iterative reservoir surveillance |
US20150169798A1 (en) * | 2012-06-15 | 2015-06-18 | Landmark Graphics Corporation | Methods and systems for gas lift rate management |
US9123161B2 (en) | 2010-08-04 | 2015-09-01 | Exxonmobil Upstream Research Company | System and method for summarizing data on an unstructured grid |
US9223594B2 (en) | 2011-07-01 | 2015-12-29 | Exxonmobil Upstream Research Company | Plug-in installer framework |
US9276959B2 (en) | 2013-11-11 | 2016-03-01 | Amazon Technologies, Inc. | Client-configurable security options for data streams |
US20160147822A1 (en) * | 2014-06-13 | 2016-05-26 | Landmark Graphics Corporation | Gold data set automation |
US9367564B2 (en) | 2010-03-12 | 2016-06-14 | Exxonmobil Upstream Research Company | Dynamic grouping of domain objects via smart groups |
US9413854B1 (en) | 2013-07-15 | 2016-08-09 | Amazon Technologies, Inc. | Network-accessible signal processing service |
US9471585B1 (en) | 2013-12-20 | 2016-10-18 | Amazon Technologies, Inc. | Decentralized de-duplication techniques for largescale data streams |
WO2017004476A1 (en) * | 2015-07-01 | 2017-01-05 | Schlumberger Technology Corporation | Fluid relationship tracking to support model dependencies |
US9595129B2 (en) | 2012-05-08 | 2017-03-14 | Exxonmobil Upstream Research Company | Canvas control for 3D data volume processing |
US9593558B2 (en) | 2010-08-24 | 2017-03-14 | Exxonmobil Upstream Research Company | System and method for planning a well path |
US9639589B1 (en) | 2013-12-20 | 2017-05-02 | Amazon Technologies, Inc. | Chained replication techniques for large-scale data streams |
US9720989B2 (en) | 2013-11-11 | 2017-08-01 | Amazon Technologies, Inc. | Dynamic partitioning techniques for data streams |
US9794135B2 (en) | 2013-11-11 | 2017-10-17 | Amazon Technologies, Inc. | Managed service for acquisition, storage and consumption of large-scale data streams |
US9818078B1 (en) * | 2013-03-12 | 2017-11-14 | Amazon Technologies, Inc. | Converting a non-workflow program to a workflow program using workflow inferencing |
US9858322B2 (en) | 2013-11-11 | 2018-01-02 | Amazon Technologies, Inc. | Data stream ingestion and persistence techniques |
US9864098B2 (en) | 2013-09-30 | 2018-01-09 | Exxonmobil Upstream Research Company | Method and system of interactive drill center and well planning evaluation and optimization |
US9874648B2 (en) | 2011-02-21 | 2018-01-23 | Exxonmobil Upstream Research Company | Reservoir connectivity analysis in a 3D earth model |
WO2019070256A1 (en) * | 2017-10-05 | 2019-04-11 | Schlumberger Technology Corporation | Petro-technical global fluid identity repository |
US10318663B2 (en) | 2011-01-26 | 2019-06-11 | Exxonmobil Upstream Research Company | Method of reservoir compartment analysis using topological structure in 3D earth model |
US10356150B1 (en) | 2014-12-15 | 2019-07-16 | Amazon Technologies, Inc. | Automated repartitioning of streaming data |
US10360194B2 (en) | 2009-03-13 | 2019-07-23 | Landmark Graphics Corporation | Systems and methods for real time data management in a collaborative environment |
US10364662B1 (en) | 2015-06-08 | 2019-07-30 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10423915B2 (en) * | 2016-06-02 | 2019-09-24 | Ge Oil & Gas Esp, Inc. | System and method for well lifecycle planning visualization |
US10423493B1 (en) | 2015-12-21 | 2019-09-24 | Amazon Technologies, Inc. | Scalable log-based continuous data protection for distributed databases |
US10567500B1 (en) | 2015-12-21 | 2020-02-18 | Amazon Technologies, Inc. | Continuous backup of data in a distributed data store |
US10584570B2 (en) | 2013-06-10 | 2020-03-10 | Exxonmobil Upstream Research Company | Interactively planning a well site |
US10621049B1 (en) | 2018-03-12 | 2020-04-14 | Amazon Technologies, Inc. | Consistent backups based on local node clock |
US10635644B2 (en) | 2013-11-11 | 2020-04-28 | Amazon Technologies, Inc. | Partition-based data stream processing framework |
US10754844B1 (en) | 2017-09-27 | 2020-08-25 | Amazon Technologies, Inc. | Efficient database snapshot generation |
US10768830B1 (en) | 2018-07-16 | 2020-09-08 | Amazon Technologies, Inc. | Streaming data service with isolated read channels |
US10798140B1 (en) | 2018-07-16 | 2020-10-06 | Amazon Technologies, Inc. | Stream data record reads using push-mode persistent connections |
US10831614B2 (en) | 2014-08-18 | 2020-11-10 | Amazon Technologies, Inc. | Visualizing restoration operation granularity for a database |
US10839351B1 (en) * | 2017-09-18 | 2020-11-17 | Amazon Technologies, Inc. | Automated workflow validation using rule-based output mapping |
US10853182B1 (en) | 2015-12-21 | 2020-12-01 | Amazon Technologies, Inc. | Scalable log-based secondary indexes for non-relational databases |
US10855754B1 (en) | 2018-07-16 | 2020-12-01 | Amazon Technologies, Inc. | Isolated read channel categories at streaming data service |
US10866962B2 (en) | 2017-09-28 | 2020-12-15 | DatalnfoCom USA, Inc. | Database management system for merging data into a database |
US10956246B1 (en) | 2018-07-16 | 2021-03-23 | Amazon Technologies, Inc. | Isolated read channel management interfaces at streaming data service |
US10990581B1 (en) | 2017-09-27 | 2021-04-27 | Amazon Technologies, Inc. | Tracking a size of a database change log |
US20210142252A1 (en) * | 2019-11-07 | 2021-05-13 | Clay Rankin | Electronic knowledge creation and management visual transformation tool |
US11042503B1 (en) | 2017-11-22 | 2021-06-22 | Amazon Technologies, Inc. | Continuous data protection and restoration |
US11042454B1 (en) | 2018-11-20 | 2021-06-22 | Amazon Technologies, Inc. | Restoration of a data source |
US11070600B1 (en) | 2018-07-16 | 2021-07-20 | Amazon Technologies, Inc. | Optimization techniques to support lagging readers at streaming data service |
US11075984B1 (en) | 2018-07-16 | 2021-07-27 | Amazon Technologies, Inc. | Workload management at streaming data service supporting persistent connections for reads |
US11126505B1 (en) | 2018-08-10 | 2021-09-21 | Amazon Technologies, Inc. | Past-state backup generator and interface for database systems |
US11182372B1 (en) | 2017-11-08 | 2021-11-23 | Amazon Technologies, Inc. | Tracking database partition change log dependencies |
US11269731B1 (en) | 2017-11-22 | 2022-03-08 | Amazon Technologies, Inc. | Continuous data protection |
US11282011B2 (en) * | 2020-04-01 | 2022-03-22 | Chevron U.S.A. Inc. | Task management interface for well operations |
US11385969B2 (en) | 2009-03-31 | 2022-07-12 | Amazon Technologies, Inc. | Cloning and recovery of data volumes |
US11755415B2 (en) | 2014-05-09 | 2023-09-12 | Amazon Technologies, Inc. | Variable data replication for storage implementing data backup |
Families Citing this family (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100250322A1 (en) * | 2009-03-27 | 2010-09-30 | Michael Roy Norwood | Simplified user interface and method for computerized task management systems |
CN102741855B (en) | 2010-02-12 | 2016-10-26 | 埃克森美孚上游研究公司 | For the method and system by Parallel Simulation model division |
WO2011103673A1 (en) * | 2010-02-25 | 2011-09-01 | Virtual Process | Unified process management system and method |
CA2808519A1 (en) * | 2010-10-22 | 2012-04-26 | Exxonmobil Upstream Research Company | Asset control and management system |
WO2014031186A1 (en) * | 2012-08-23 | 2014-02-27 | Landmark Graphics Corporation | Well planning workflow system, method and computer-program product |
WO2014150580A1 (en) * | 2013-03-15 | 2014-09-25 | Exxonmobil Upstream Research Company | Method for geophysical modeling of subsurface volumes |
CN103617201A (en) * | 2013-11-14 | 2014-03-05 | 陕西理工学院 | Visualization method and visualization model |
RU2016125866A (en) | 2014-02-26 | 2018-03-27 | Лэндмарк Графикс Корпорейшн | OIL PRODUCTION NETWORK TECHNOLOGY |
US10815758B2 (en) * | 2015-01-16 | 2020-10-27 | Schlumberger Technology Corporation | Oilfield service selector |
CN115345409A (en) * | 2015-03-06 | 2022-11-15 | 哈佛蒸汽锅炉检验和保险公司 | Risk assessment for drilling and completion operations |
US10762471B1 (en) * | 2017-01-09 | 2020-09-01 | Palantir Technologies Inc. | Automating management of integrated workflows based on disparate subsidiary data sources |
US10878350B1 (en) * | 2018-06-11 | 2020-12-29 | Palantir Technologies Inc. | Methods and systems for providing a user interface for managing parts production and delivery statuses |
CN110765098B (en) * | 2019-09-02 | 2020-10-02 | 望海康信(北京)科技股份公司 | Flow operation prediction system and method |
WO2022093730A1 (en) * | 2020-10-30 | 2022-05-05 | Schlumberger Technology Corporation | Centrally collecting and tracking model update inputs |
CN112612568B (en) * | 2020-12-25 | 2022-06-28 | 中电金信软件有限公司 | Workflow task item display method and device and electronic equipment |
Citations (47)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5826239A (en) * | 1996-12-17 | 1998-10-20 | Hewlett-Packard Company | Distributed workflow resource management system and method |
US6086617A (en) * | 1997-07-18 | 2000-07-11 | Engineous Software, Inc. | User directed heuristic design optimization search |
US6236894B1 (en) * | 1997-12-19 | 2001-05-22 | Atlantic Richfield Company | Petroleum production optimization utilizing adaptive network and genetic algorithm techniques |
US6253206B1 (en) * | 1999-08-20 | 2001-06-26 | Inroads Technology, Inc. | Method and apparatus for a commercial network system designed to facilitate, manage and support the implementation and integration of technology systems |
US6266619B1 (en) * | 1999-07-20 | 2001-07-24 | Halliburton Energy Services, Inc. | System and method for real time reservoir management |
US6277434B1 (en) * | 2000-05-30 | 2001-08-21 | Sally E. Matluk-Boisseau | Pet food product and methods of product manufacture and distribution |
US6308163B1 (en) * | 1999-03-16 | 2001-10-23 | Hewlett-Packard Company | System and method for enterprise workflow resource management |
US20020038217A1 (en) * | 2000-04-07 | 2002-03-28 | Alan Young | System and method for integrated data analysis and management |
US6367548B1 (en) * | 1999-03-05 | 2002-04-09 | Bj Services Company | Diversion treatment method |
US20020070953A1 (en) * | 2000-05-04 | 2002-06-13 | Barg Timothy A. | Systems and methods for visualizing and analyzing conditioned data |
US20020078432A1 (en) * | 2000-09-01 | 2002-06-20 | Dietrich Charisius | Methods and systems for improving a workflow based on data mined from plans created from the workflow |
US6424948B1 (en) * | 1999-02-19 | 2002-07-23 | Guozhu Dong | Declarative workflow system supporting side-effects |
US6434435B1 (en) * | 1997-02-21 | 2002-08-13 | Baker Hughes Incorporated | Application of adaptive object-oriented optimization software to an automatic optimization oilfield hydrocarbon production management system |
US20020161840A1 (en) * | 2001-02-20 | 2002-10-31 | Willcox William J. | Adapter for interfacing with a workflow engine |
US20020177955A1 (en) * | 2000-09-28 | 2002-11-28 | Younes Jalali | Completions architecture |
US20020188644A1 (en) * | 2001-06-08 | 2002-12-12 | Verano | Workflow automated task component manager |
US6519568B1 (en) * | 1999-06-15 | 2003-02-11 | Schlumberger Technology Corporation | System and method for electronic data delivery |
US6549854B1 (en) * | 1999-02-12 | 2003-04-15 | Schlumberger Technology Corporation | Uncertainty constrained subsurface modeling |
US6678744B2 (en) * | 1997-10-09 | 2004-01-13 | Ericsson Inc. | Application wrapper methods and systems |
US20040010591A1 (en) * | 2002-07-11 | 2004-01-15 | Richard Sinn | Employing wrapper profiles |
US6686423B1 (en) * | 1999-11-13 | 2004-02-03 | Basf Aktiengesellschaft | Method for carrying out the anionic polymerization of vinylaromatic monomers |
US6691151B1 (en) * | 1999-01-05 | 2004-02-10 | Sri International | Unified messaging methods and systems for communication and cooperation among distributed agents in a computing environment |
US20040220790A1 (en) * | 2003-04-30 | 2004-11-04 | Cullick Alvin Stanley | Method and system for scenario and case decision management |
US6816902B1 (en) * | 1998-12-01 | 2004-11-09 | International Business Machines Corporation | Method and system for improving workflow performance in workflow application systems |
US20040230941A1 (en) * | 2003-01-17 | 2004-11-18 | Marin Mike A. | Component integrator |
US6826483B1 (en) * | 1999-10-13 | 2004-11-30 | The Trustees Of Columbia University In The City Of New York | Petroleum reservoir simulation and characterization system and method |
US20050015741A1 (en) * | 2001-12-12 | 2005-01-20 | Dirk Langkafel | System and method for tracing and/or evaluating the exchange of information |
US6853921B2 (en) * | 1999-07-20 | 2005-02-08 | Halliburton Energy Services, Inc. | System and method for real time reservoir management |
US6868423B2 (en) * | 2001-07-18 | 2005-03-15 | Hitachi, Ltd. | Production and preprocessing system for data mining |
US6873267B1 (en) * | 1999-09-29 | 2005-03-29 | Weatherford/Lamb, Inc. | Methods and apparatus for monitoring and controlling oil and gas production wells from a remote location |
US6890929B2 (en) * | 1998-06-19 | 2005-05-10 | Pfizer, Inc. | Pyrrolo [2,3-D] pyrimidine compounds |
US20060015619A1 (en) * | 2004-06-30 | 2006-01-19 | Siebel Systems, Inc. | Access and synchronization with enterprise applications using remote hosted solution |
US20060074732A1 (en) * | 2004-10-01 | 2006-04-06 | Microsoft Corporation | Componentized and extensible workflow model |
US7047535B2 (en) * | 2001-07-30 | 2006-05-16 | International Business Machines Corporation | Method, system, and program for performing workflow related operations using an application programming interface |
US7058933B2 (en) * | 2002-09-11 | 2006-06-06 | Sun Microsystems, Inc. | Extending custom application development environment modules to a second application development environment |
US20070109223A1 (en) * | 2003-06-24 | 2007-05-17 | Toshikazu Wakabayashi | Plasma display apparatus and driving method thereof |
US7236939B2 (en) * | 2001-03-31 | 2007-06-26 | Hewlett-Packard Development Company, L.P. | Peer-to-peer inter-enterprise collaborative process management method and system |
US20070179767A1 (en) * | 2006-01-31 | 2007-08-02 | Alvin Stanley Cullick | Methods, systems, and computer-readable media for fast updating of oil and gas field production models with physical and proxy simulators |
US20070179766A1 (en) * | 2006-01-31 | 2007-08-02 | Landmark Graphics Corporation | Methods, systems, and computer-readable media for real-time oil and gas field production optimization using a proxy simulator |
US20070179768A1 (en) * | 2006-01-31 | 2007-08-02 | Cullick Alvin S | Methods, systems, and computer readable media for fast updating of oil and gas field production models with physical and proxy simulators |
US7289966B2 (en) * | 2001-08-14 | 2007-10-30 | Norman Ken Ouchi | Method and system for adapting the execution of a workflow route |
US20070265895A1 (en) * | 2006-05-09 | 2007-11-15 | Sap Ag | Ad-hoc workflow as a business process template |
US20070271039A1 (en) * | 2006-01-20 | 2007-11-22 | Ella Richard G | Dynamic Production System Management |
US7369973B2 (en) * | 2000-06-29 | 2008-05-06 | Object Reservoir, Inc. | Method and system for representing reservoir systems |
US7373976B2 (en) * | 2004-11-18 | 2008-05-20 | Casey Danny M | Well production optimizing system |
US20080133194A1 (en) * | 2006-10-30 | 2008-06-05 | Schlumberger Technology Corporation | System and method for performing oilfield simulation operations |
US7483879B2 (en) * | 2003-01-17 | 2009-01-27 | International Business Machines Corporation | System and method for accessing non-compatible content repositories |
Family Cites Families (20)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US2007109A (en) * | 1931-06-20 | 1935-07-02 | Sullivan Machinery Co | Loading machine |
US5812068A (en) | 1994-12-12 | 1998-09-22 | Baker Hughes Incorporated | Drilling system with downhole apparatus for determining parameters of interest and for adjusting drilling direction in response thereto |
US6980940B1 (en) * | 2000-02-22 | 2005-12-27 | Schlumberger Technology Corp. | Intergrated reservoir optimization |
CA2419272A1 (en) | 2000-08-22 | 2002-02-28 | Deere & Company | System and method for developing a farm management plan for production agriculture |
AU2002239619A1 (en) * | 2000-12-08 | 2002-06-18 | Peter J. Ortoleva | Methods for modeling multi-dimensional domains using information theory to resolve gaps in data and in theories |
AU2002252222A1 (en) * | 2001-03-08 | 2002-09-24 | Richard M. Adler | System for analyzing strategic business decisions |
US6980929B2 (en) | 2001-04-18 | 2005-12-27 | Baker Hughes Incorporated | Well data collection system and method |
FR2837947B1 (en) * | 2002-04-02 | 2004-05-28 | Inst Francais Du Petrole | METHOD FOR QUANTIFYING THE UNCERTAINTIES RELATED TO CONTINUOUS AND DESCRIPTIVE PARAMETERS OF A MEDIUM BY CONSTRUCTION OF EXPERIMENT PLANS AND STATISTICAL ANALYSIS |
US7512543B2 (en) * | 2002-05-29 | 2009-03-31 | Schlumberger Technology Corporation | Tools for decision-making in reservoir risk management |
US20040073505A1 (en) * | 2002-10-09 | 2004-04-15 | James Foley Wright | Method for performing monte carlo risk analysis of business scenarios |
US7539625B2 (en) * | 2004-03-17 | 2009-05-26 | Schlumberger Technology Corporation | Method and apparatus and program storage device including an integrated well planning workflow control system with process dependencies |
US7725302B2 (en) * | 2003-12-02 | 2010-05-25 | Schlumberger Technology Corporation | Method and system and program storage device for generating an SWPM-MDT workflow in response to a user objective and executing the workflow to produce a reservoir response model |
US7172020B2 (en) * | 2004-03-05 | 2007-02-06 | Tseytlin Software Consulting Inc. | Oil production optimization and enhanced recovery method and apparatus for oil fields with high gas-to-oil ratio |
US7548873B2 (en) * | 2004-03-17 | 2009-06-16 | Schlumberger Technology Corporation | Method system and program storage device for automatically calculating and displaying time and cost data in a well planning system using a Monte Carlo simulation software |
CA2575810A1 (en) * | 2004-08-02 | 2006-02-16 | Schlumberger Canada Limited | Method apparatus and system for visualization of probabilistic models |
MX2007016574A (en) * | 2005-07-27 | 2008-03-04 | Exxonmobil Upstream Res Co | Well modeling associated with extraction of hydrocarbons from subsurface formations. |
US8311789B2 (en) * | 2006-02-24 | 2012-11-13 | Saudi Arabian Oil Company | Monte Carlo simulation of well logging data |
EP2004953B1 (en) | 2006-04-07 | 2009-10-07 | Shell Internationale Research Maatschappij B.V. | Method for optimising the production of a cluster of wells |
US8000946B2 (en) * | 2006-09-20 | 2011-08-16 | The Boeing Company | Discrete event simulation with constraint based scheduling analysis |
WO2009061903A2 (en) * | 2007-11-10 | 2009-05-14 | Landmark Graphics Corporation | Systems and methods for workflow automation, adaptation and integration |
-
2008
- 2008-11-06 WO PCT/US2008/082610 patent/WO2009061903A2/en active Search and Examination
- 2008-11-06 AU AU2008323932A patent/AU2008323932B2/en not_active Ceased
- 2008-11-06 CA CA2705319A patent/CA2705319C/en active Active
- 2008-11-06 EP EP20130153520 patent/EP2605191A3/en not_active Ceased
- 2008-11-06 EP EP08848362A patent/EP2208173A4/en not_active Withdrawn
- 2008-11-06 MX MX2010005116A patent/MX2010005116A/en unknown
- 2008-11-06 BR BRPI0817402A patent/BRPI0817402A2/en not_active IP Right Cessation
- 2008-11-06 CN CN2008801153401A patent/CN102007504A/en active Pending
- 2008-11-07 US US12/266,766 patent/US20090125362A1/en not_active Abandoned
-
2010
- 2010-07-23 US US12/842,772 patent/US9128693B2/en active Active
Patent Citations (53)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5826239A (en) * | 1996-12-17 | 1998-10-20 | Hewlett-Packard Company | Distributed workflow resource management system and method |
US6434435B1 (en) * | 1997-02-21 | 2002-08-13 | Baker Hughes Incorporated | Application of adaptive object-oriented optimization software to an automatic optimization oilfield hydrocarbon production management system |
US6086617A (en) * | 1997-07-18 | 2000-07-11 | Engineous Software, Inc. | User directed heuristic design optimization search |
US6678744B2 (en) * | 1997-10-09 | 2004-01-13 | Ericsson Inc. | Application wrapper methods and systems |
US6236894B1 (en) * | 1997-12-19 | 2001-05-22 | Atlantic Richfield Company | Petroleum production optimization utilizing adaptive network and genetic algorithm techniques |
US6890929B2 (en) * | 1998-06-19 | 2005-05-10 | Pfizer, Inc. | Pyrrolo [2,3-D] pyrimidine compounds |
US6816902B1 (en) * | 1998-12-01 | 2004-11-09 | International Business Machines Corporation | Method and system for improving workflow performance in workflow application systems |
US6691151B1 (en) * | 1999-01-05 | 2004-02-10 | Sri International | Unified messaging methods and systems for communication and cooperation among distributed agents in a computing environment |
US6549854B1 (en) * | 1999-02-12 | 2003-04-15 | Schlumberger Technology Corporation | Uncertainty constrained subsurface modeling |
US6424948B1 (en) * | 1999-02-19 | 2002-07-23 | Guozhu Dong | Declarative workflow system supporting side-effects |
US6367548B1 (en) * | 1999-03-05 | 2002-04-09 | Bj Services Company | Diversion treatment method |
US6308163B1 (en) * | 1999-03-16 | 2001-10-23 | Hewlett-Packard Company | System and method for enterprise workflow resource management |
US6519568B1 (en) * | 1999-06-15 | 2003-02-11 | Schlumberger Technology Corporation | System and method for electronic data delivery |
US6853921B2 (en) * | 1999-07-20 | 2005-02-08 | Halliburton Energy Services, Inc. | System and method for real time reservoir management |
US6356844B2 (en) * | 1999-07-20 | 2002-03-12 | Halliburton Energy Services, Inc. | System and method for real time reservoir management |
US7079952B2 (en) * | 1999-07-20 | 2006-07-18 | Halliburton Energy Services, Inc. | System and method for real time reservoir management |
US6266619B1 (en) * | 1999-07-20 | 2001-07-24 | Halliburton Energy Services, Inc. | System and method for real time reservoir management |
US20010013033A1 (en) * | 1999-08-20 | 2001-08-09 | Burton Tom C. | Method and apparatus for a commercial network system designed to facilitate, manage and support the implementation and integration of technology systems |
US6253206B1 (en) * | 1999-08-20 | 2001-06-26 | Inroads Technology, Inc. | Method and apparatus for a commercial network system designed to facilitate, manage and support the implementation and integration of technology systems |
US6873267B1 (en) * | 1999-09-29 | 2005-03-29 | Weatherford/Lamb, Inc. | Methods and apparatus for monitoring and controlling oil and gas production wells from a remote location |
US6826483B1 (en) * | 1999-10-13 | 2004-11-30 | The Trustees Of Columbia University In The City Of New York | Petroleum reservoir simulation and characterization system and method |
US6686423B1 (en) * | 1999-11-13 | 2004-02-03 | Basf Aktiengesellschaft | Method for carrying out the anionic polymerization of vinylaromatic monomers |
US20020038217A1 (en) * | 2000-04-07 | 2002-03-28 | Alan Young | System and method for integrated data analysis and management |
US20020070953A1 (en) * | 2000-05-04 | 2002-06-13 | Barg Timothy A. | Systems and methods for visualizing and analyzing conditioned data |
US6277434B1 (en) * | 2000-05-30 | 2001-08-21 | Sally E. Matluk-Boisseau | Pet food product and methods of product manufacture and distribution |
US7369973B2 (en) * | 2000-06-29 | 2008-05-06 | Object Reservoir, Inc. | Method and system for representing reservoir systems |
US20020078432A1 (en) * | 2000-09-01 | 2002-06-20 | Dietrich Charisius | Methods and systems for improving a workflow based on data mined from plans created from the workflow |
US6938240B2 (en) * | 2000-09-01 | 2005-08-30 | Borland Software Corporation | Methods and systems for improving a workflow based on data mined from plans created from the workflow |
US20020177955A1 (en) * | 2000-09-28 | 2002-11-28 | Younes Jalali | Completions architecture |
US20020161840A1 (en) * | 2001-02-20 | 2002-10-31 | Willcox William J. | Adapter for interfacing with a workflow engine |
US7236939B2 (en) * | 2001-03-31 | 2007-06-26 | Hewlett-Packard Development Company, L.P. | Peer-to-peer inter-enterprise collaborative process management method and system |
US20020188644A1 (en) * | 2001-06-08 | 2002-12-12 | Verano | Workflow automated task component manager |
US6868423B2 (en) * | 2001-07-18 | 2005-03-15 | Hitachi, Ltd. | Production and preprocessing system for data mining |
US7047535B2 (en) * | 2001-07-30 | 2006-05-16 | International Business Machines Corporation | Method, system, and program for performing workflow related operations using an application programming interface |
US7289966B2 (en) * | 2001-08-14 | 2007-10-30 | Norman Ken Ouchi | Method and system for adapting the execution of a workflow route |
US20050015741A1 (en) * | 2001-12-12 | 2005-01-20 | Dirk Langkafel | System and method for tracing and/or evaluating the exchange of information |
US20040010591A1 (en) * | 2002-07-11 | 2004-01-15 | Richard Sinn | Employing wrapper profiles |
US7058933B2 (en) * | 2002-09-11 | 2006-06-06 | Sun Microsystems, Inc. | Extending custom application development environment modules to a second application development environment |
US20040230941A1 (en) * | 2003-01-17 | 2004-11-18 | Marin Mike A. | Component integrator |
US7483879B2 (en) * | 2003-01-17 | 2009-01-27 | International Business Machines Corporation | System and method for accessing non-compatible content repositories |
US7415716B2 (en) * | 2003-01-17 | 2008-08-19 | International Business Machines Corporation | Component integrator |
US20040220790A1 (en) * | 2003-04-30 | 2004-11-04 | Cullick Alvin Stanley | Method and system for scenario and case decision management |
US20070109223A1 (en) * | 2003-06-24 | 2007-05-17 | Toshikazu Wakabayashi | Plasma display apparatus and driving method thereof |
US20060015619A1 (en) * | 2004-06-30 | 2006-01-19 | Siebel Systems, Inc. | Access and synchronization with enterprise applications using remote hosted solution |
US20060074732A1 (en) * | 2004-10-01 | 2006-04-06 | Microsoft Corporation | Componentized and extensible workflow model |
US7373976B2 (en) * | 2004-11-18 | 2008-05-20 | Casey Danny M | Well production optimizing system |
US20070271039A1 (en) * | 2006-01-20 | 2007-11-22 | Ella Richard G | Dynamic Production System Management |
US20070192072A1 (en) * | 2006-01-31 | 2007-08-16 | Cullick Alvin S | Methods, systems, and computer-readable media for real-time oil and gas field production optimization using a proxy simulator |
US20070179768A1 (en) * | 2006-01-31 | 2007-08-02 | Cullick Alvin S | Methods, systems, and computer readable media for fast updating of oil and gas field production models with physical and proxy simulators |
US20070179766A1 (en) * | 2006-01-31 | 2007-08-02 | Landmark Graphics Corporation | Methods, systems, and computer-readable media for real-time oil and gas field production optimization using a proxy simulator |
US20070179767A1 (en) * | 2006-01-31 | 2007-08-02 | Alvin Stanley Cullick | Methods, systems, and computer-readable media for fast updating of oil and gas field production models with physical and proxy simulators |
US20070265895A1 (en) * | 2006-05-09 | 2007-11-15 | Sap Ag | Ad-hoc workflow as a business process template |
US20080133194A1 (en) * | 2006-10-30 | 2008-06-05 | Schlumberger Technology Corporation | System and method for performing oilfield simulation operations |
Non-Patent Citations (9)
Title |
---|
Ellis, Clarence et al.(Dynamic Change Within Workflow Systems; COOCS 1995, ACM, Pages 10-21) * |
Han, Yanbo et al. (A Taxonomy of Adative Workflow Management; 1998 ACM Conference on Computer Supported Cooperative Work, 1998) * |
Heinl, Petra et al.(A Comprehensive Approach to Flexibility in Workflow Management Systems; ACM, 1999, Pages 79-88) * |
Hiramatsu, Keiko et al., (Interworkflow System: Coordination of Each Workflow System Among Multiple Organizations; Third International Conference of Cooperative Information Systems, 1998) * |
Meijler, Theo Dirk et al.(Realising Run-time Adaptable Workflow by means of Reflection in the Baan Workflow Engine; CSCW, 1998) * |
Merz, M. et al., (Interorganizational Workflow Management with Mobile Agents in COSM; Conference on the Practical Application of Agents and Multi-Agency Systems, PAAM'96, 1996) * |
Schulz, Karsten et al. (Architecting Cross-Organizatinoal B2B Interactions; Conference on Enterprise Distributed Object Computing, 2000) * |
Sladek, Aija et al. (Modeling Inter-Organizational Workflows; Proceedings International Symposium on Applied Corporate Computing, ISACC'96, October, 1996) * |
Voorhoeve M. et al.(Ad-hoc Workflow: Problem and Solutions; IEEE, 1997, Pages 36-40) * |
Cited By (105)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110022435A1 (en) * | 2007-11-10 | 2011-01-27 | Landmark Graphics Corporation, A Halliburton Company | Systems and Methods for Workflow Automation, Adaptation and Integration |
US9128693B2 (en) * | 2007-11-10 | 2015-09-08 | Landmark Graphics Corporation | Systems and methods for workflow automation, adaptation and integration |
US9026417B2 (en) | 2007-12-13 | 2015-05-05 | Exxonmobil Upstream Research Company | Iterative reservoir surveillance |
US8554778B2 (en) | 2008-04-04 | 2013-10-08 | Landmark Graphics Corporation | Systems and methods for correlating meta-data model representations and asset-logic model representations |
US10552391B2 (en) | 2008-04-04 | 2020-02-04 | Landmark Graphics Corporation | Systems and methods for real time data management in a collaborative environment |
US8229938B2 (en) | 2008-04-04 | 2012-07-24 | Landmark Graphics Corporation | Systems and methods for correlating meta-data model representations and asset-logic model representations |
US20100005111A1 (en) * | 2008-04-04 | 2010-01-07 | Landmark Graphics Corporation, A Halliburton Company | Systems and Methods for Correlating Meta-Data Model Representations and Asset-Logic Model Representations |
US8884964B2 (en) | 2008-04-22 | 2014-11-11 | Exxonmobil Upstream Research Company | Functional-based knowledge analysis in a 2D and 3D visual environment |
US20110172976A1 (en) * | 2008-10-01 | 2011-07-14 | Budiman Benny S | Robust Well Trajectory Planning |
US8892407B2 (en) | 2008-10-01 | 2014-11-18 | Exxonmobil Upstream Research Company | Robust well trajectory planning |
US20110153300A1 (en) * | 2008-11-06 | 2011-06-23 | Holl James E | System and Method For Planning A Drilling Operation |
US8849640B2 (en) | 2008-11-06 | 2014-09-30 | Exxonmobil Upstream Research Company | System and method for planning a drilling operation |
US20100192077A1 (en) * | 2009-01-26 | 2010-07-29 | Raytheon Company | Parent/Child Control System for a Workflow Automation Tool |
US10360194B2 (en) | 2009-03-13 | 2019-07-23 | Landmark Graphics Corporation | Systems and methods for real time data management in a collaborative environment |
US11385969B2 (en) | 2009-03-31 | 2022-07-12 | Amazon Technologies, Inc. | Cloning and recovery of data volumes |
US11914486B2 (en) | 2009-03-31 | 2024-02-27 | Amazon Technologies, Inc. | Cloning and recovery of data volumes |
US8429671B2 (en) * | 2009-10-21 | 2013-04-23 | Exxonmobil Upstream Research Company | Integrated workflow builder for disparate computer programs |
US20110093864A1 (en) * | 2009-10-21 | 2011-04-21 | Wood Stephen B | Integrated Workflow Builder |
US8931580B2 (en) | 2010-02-03 | 2015-01-13 | Exxonmobil Upstream Research Company | Method for using dynamic target region for well path/drill center optimization |
US20110218775A1 (en) * | 2010-03-08 | 2011-09-08 | Czernuszenko Marek K | System and Method For Providing Data Corresponding To Physical Objects |
US8731872B2 (en) | 2010-03-08 | 2014-05-20 | Exxonmobil Upstream Research Company | System and method for providing data corresponding to physical objects |
US9367564B2 (en) | 2010-03-12 | 2016-06-14 | Exxonmobil Upstream Research Company | Dynamic grouping of domain objects via smart groups |
US8731887B2 (en) | 2010-04-12 | 2014-05-20 | Exxonmobile Upstream Research Company | System and method for obtaining a model of data describing a physical structure |
US8727017B2 (en) | 2010-04-22 | 2014-05-20 | Exxonmobil Upstream Research Company | System and method for obtaining data on an unstructured grid |
US8731873B2 (en) | 2010-04-26 | 2014-05-20 | Exxonmobil Upstream Research Company | System and method for providing data corresponding to physical objects |
US9123161B2 (en) | 2010-08-04 | 2015-09-01 | Exxonmobil Upstream Research Company | System and method for summarizing data on an unstructured grid |
US8731875B2 (en) | 2010-08-13 | 2014-05-20 | Exxonmobil Upstream Research Company | System and method for providing data corresponding to physical objects |
US9593558B2 (en) | 2010-08-24 | 2017-03-14 | Exxonmobil Upstream Research Company | System and method for planning a well path |
US9229603B2 (en) * | 2010-12-28 | 2016-01-05 | Schlumberger Technology Corporation | Methods, systems, apparatuses, and computer-readable mediums for provisioning petrotechnical workflows in a cloud computing environment |
US20120166967A1 (en) * | 2010-12-28 | 2012-06-28 | Schlumberger Technology Corporation | Methods, systems, apparatuses, and computer-readable mediums for provisioning petrotechnical workflows in a cloud computing environment |
US10318663B2 (en) | 2011-01-26 | 2019-06-11 | Exxonmobil Upstream Research Company | Method of reservoir compartment analysis using topological structure in 3D earth model |
US9874648B2 (en) | 2011-02-21 | 2018-01-23 | Exxonmobil Upstream Research Company | Reservoir connectivity analysis in a 3D earth model |
CN103392054A (en) * | 2011-02-23 | 2013-11-13 | 兰德马克绘图国际公司 | Method and systems of determining viable hydraulic fracture scenarios |
AU2011360239B2 (en) * | 2011-02-23 | 2014-10-23 | Landmark Graphics Corporation | Method and systems of determining viable hydraulic fracture scenarios |
US20130304444A1 (en) * | 2011-02-23 | 2013-11-14 | Landmark Graphics Corporation | Method and systems of determining viable hydraulic fracture scenarios |
US8855988B2 (en) * | 2011-02-23 | 2014-10-07 | Landmark Graphics Corporation | Method and systems of determining viable hydraulic fracture scenarios |
US20120317209A1 (en) * | 2011-06-13 | 2012-12-13 | Jason Rex Briggs | System and method for managing and implementing procedures and practices |
US10032121B2 (en) * | 2011-06-13 | 2018-07-24 | Marketing Evolution | System and method for managing and implementing procedures and practices |
US9223594B2 (en) | 2011-07-01 | 2015-12-29 | Exxonmobil Upstream Research Company | Plug-in installer framework |
US9595129B2 (en) | 2012-05-08 | 2017-03-14 | Exxonmobil Upstream Research Company | Canvas control for 3D data volume processing |
US20150169798A1 (en) * | 2012-06-15 | 2015-06-18 | Landmark Graphics Corporation | Methods and systems for gas lift rate management |
US20140214476A1 (en) * | 2013-01-31 | 2014-07-31 | Halliburton Energy Services, Inc. | Data initialization for a subterranean operation |
US9818078B1 (en) * | 2013-03-12 | 2017-11-14 | Amazon Technologies, Inc. | Converting a non-workflow program to a workflow program using workflow inferencing |
US20140343982A1 (en) * | 2013-05-14 | 2014-11-20 | Landmark Graphics Corporation | Methods and systems related to workflow mentoring |
US10584570B2 (en) | 2013-06-10 | 2020-03-10 | Exxonmobil Upstream Research Company | Interactively planning a well site |
US9413854B1 (en) | 2013-07-15 | 2016-08-09 | Amazon Technologies, Inc. | Network-accessible signal processing service |
US9864098B2 (en) | 2013-09-30 | 2018-01-09 | Exxonmobil Upstream Research Company | Method and system of interactive drill center and well planning evaluation and optimization |
US9720989B2 (en) | 2013-11-11 | 2017-08-01 | Amazon Technologies, Inc. | Dynamic partitioning techniques for data streams |
US10795905B2 (en) | 2013-11-11 | 2020-10-06 | Amazon Technologies, Inc. | Data stream ingestion and persistence techniques |
US9794135B2 (en) | 2013-11-11 | 2017-10-17 | Amazon Technologies, Inc. | Managed service for acquisition, storage and consumption of large-scale data streams |
US9276959B2 (en) | 2013-11-11 | 2016-03-01 | Amazon Technologies, Inc. | Client-configurable security options for data streams |
US9858322B2 (en) | 2013-11-11 | 2018-01-02 | Amazon Technologies, Inc. | Data stream ingestion and persistence techniques |
US10635644B2 (en) | 2013-11-11 | 2020-04-28 | Amazon Technologies, Inc. | Partition-based data stream processing framework |
US10691716B2 (en) | 2013-11-11 | 2020-06-23 | Amazon Technologies, Inc. | Dynamic partitioning techniques for data streams |
US9639589B1 (en) | 2013-12-20 | 2017-05-02 | Amazon Technologies, Inc. | Chained replication techniques for large-scale data streams |
US10467105B2 (en) | 2013-12-20 | 2019-11-05 | Amazon Technologies, Inc. | Chained replication techniques for large-scale data streams |
US9471585B1 (en) | 2013-12-20 | 2016-10-18 | Amazon Technologies, Inc. | Decentralized de-duplication techniques for largescale data streams |
CN103824162A (en) * | 2014-02-28 | 2014-05-28 | 北京航空航天大学 | Reliability and performance integrated flexible workflow implementing method based on instruction chain |
US11755415B2 (en) | 2014-05-09 | 2023-09-12 | Amazon Technologies, Inc. | Variable data replication for storage implementing data backup |
US20160147822A1 (en) * | 2014-06-13 | 2016-05-26 | Landmark Graphics Corporation | Gold data set automation |
US9633067B2 (en) * | 2014-06-13 | 2017-04-25 | Landmark Graphics Corporation | Gold data set automation |
US10831614B2 (en) | 2014-08-18 | 2020-11-10 | Amazon Technologies, Inc. | Visualizing restoration operation granularity for a database |
US10356150B1 (en) | 2014-12-15 | 2019-07-16 | Amazon Technologies, Inc. | Automated repartitioning of streaming data |
US10565663B1 (en) | 2015-06-08 | 2020-02-18 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10577894B1 (en) | 2015-06-08 | 2020-03-03 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10364662B1 (en) | 2015-06-08 | 2019-07-30 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10607170B1 (en) | 2015-06-08 | 2020-03-31 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US11536121B1 (en) | 2015-06-08 | 2022-12-27 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10851636B1 (en) | 2015-06-08 | 2020-12-01 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10643146B1 (en) | 2015-06-08 | 2020-05-05 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10677037B1 (en) | 2015-06-08 | 2020-06-09 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10410298B1 (en) | 2015-06-08 | 2019-09-10 | DataInfoCom USA, Inc. | Systems and methods for analyzing resource production |
US10415362B1 (en) | 2015-06-08 | 2019-09-17 | DataInfoCom USA Inc. | Systems and methods for analyzing resource production |
WO2017004476A1 (en) * | 2015-07-01 | 2017-01-05 | Schlumberger Technology Corporation | Fluid relationship tracking to support model dependencies |
US11153380B2 (en) | 2015-12-21 | 2021-10-19 | Amazon Technologies, Inc. | Continuous backup of data in a distributed data store |
US10853182B1 (en) | 2015-12-21 | 2020-12-01 | Amazon Technologies, Inc. | Scalable log-based secondary indexes for non-relational databases |
US10567500B1 (en) | 2015-12-21 | 2020-02-18 | Amazon Technologies, Inc. | Continuous backup of data in a distributed data store |
US10423493B1 (en) | 2015-12-21 | 2019-09-24 | Amazon Technologies, Inc. | Scalable log-based continuous data protection for distributed databases |
US10423915B2 (en) * | 2016-06-02 | 2019-09-24 | Ge Oil & Gas Esp, Inc. | System and method for well lifecycle planning visualization |
US10839351B1 (en) * | 2017-09-18 | 2020-11-17 | Amazon Technologies, Inc. | Automated workflow validation using rule-based output mapping |
US10990581B1 (en) | 2017-09-27 | 2021-04-27 | Amazon Technologies, Inc. | Tracking a size of a database change log |
US10754844B1 (en) | 2017-09-27 | 2020-08-25 | Amazon Technologies, Inc. | Efficient database snapshot generation |
US10866962B2 (en) | 2017-09-28 | 2020-12-15 | DatalnfoCom USA, Inc. | Database management system for merging data into a database |
US11803679B2 (en) | 2017-10-05 | 2023-10-31 | Schlumberger Technology Corporation | Petro-technical global fluid identity repository |
WO2019070256A1 (en) * | 2017-10-05 | 2019-04-11 | Schlumberger Technology Corporation | Petro-technical global fluid identity repository |
US11182372B1 (en) | 2017-11-08 | 2021-11-23 | Amazon Technologies, Inc. | Tracking database partition change log dependencies |
US11042503B1 (en) | 2017-11-22 | 2021-06-22 | Amazon Technologies, Inc. | Continuous data protection and restoration |
US11860741B2 (en) | 2017-11-22 | 2024-01-02 | Amazon Technologies, Inc. | Continuous data protection |
US11269731B1 (en) | 2017-11-22 | 2022-03-08 | Amazon Technologies, Inc. | Continuous data protection |
US10621049B1 (en) | 2018-03-12 | 2020-04-14 | Amazon Technologies, Inc. | Consistent backups based on local node clock |
US10768830B1 (en) | 2018-07-16 | 2020-09-08 | Amazon Technologies, Inc. | Streaming data service with isolated read channels |
US11675501B2 (en) | 2018-07-16 | 2023-06-13 | Amazon Technologies, Inc. | Streaming data service with isolated read channels |
US11075984B1 (en) | 2018-07-16 | 2021-07-27 | Amazon Technologies, Inc. | Workload management at streaming data service supporting persistent connections for reads |
US10798140B1 (en) | 2018-07-16 | 2020-10-06 | Amazon Technologies, Inc. | Stream data record reads using push-mode persistent connections |
US11070600B1 (en) | 2018-07-16 | 2021-07-20 | Amazon Technologies, Inc. | Optimization techniques to support lagging readers at streaming data service |
US11509700B2 (en) | 2018-07-16 | 2022-11-22 | Amazon Technologies, Inc. | Stream data record reads using push-mode persistent connections |
US10855754B1 (en) | 2018-07-16 | 2020-12-01 | Amazon Technologies, Inc. | Isolated read channel categories at streaming data service |
US10956246B1 (en) | 2018-07-16 | 2021-03-23 | Amazon Technologies, Inc. | Isolated read channel management interfaces at streaming data service |
US11621999B2 (en) | 2018-07-16 | 2023-04-04 | Amazon Technologies, Inc. | Isolated read channel categories at streaming data service |
US11126505B1 (en) | 2018-08-10 | 2021-09-21 | Amazon Technologies, Inc. | Past-state backup generator and interface for database systems |
US11579981B2 (en) | 2018-08-10 | 2023-02-14 | Amazon Technologies, Inc. | Past-state backup generator and interface for database systems |
US11042454B1 (en) | 2018-11-20 | 2021-06-22 | Amazon Technologies, Inc. | Restoration of a data source |
US11663542B2 (en) * | 2019-11-07 | 2023-05-30 | Clay Rankin | Electronic knowledge creation and management visual transformation tool |
US20210142252A1 (en) * | 2019-11-07 | 2021-05-13 | Clay Rankin | Electronic knowledge creation and management visual transformation tool |
US11282011B2 (en) * | 2020-04-01 | 2022-03-22 | Chevron U.S.A. Inc. | Task management interface for well operations |
Also Published As
Publication number | Publication date |
---|---|
WO2009061903A3 (en) | 2010-08-12 |
CN102007504A (en) | 2011-04-06 |
CA2705319A1 (en) | 2009-05-14 |
CA2705319C (en) | 2019-01-15 |
AU2008323932A1 (en) | 2009-05-14 |
AU2008323932B2 (en) | 2013-06-20 |
EP2605191A2 (en) | 2013-06-19 |
EP2605191A3 (en) | 2013-08-21 |
BRPI0817402A2 (en) | 2019-09-24 |
EP2208173A2 (en) | 2010-07-21 |
EP2208173A4 (en) | 2012-08-08 |
MX2010005116A (en) | 2010-09-09 |
US9128693B2 (en) | 2015-09-08 |
WO2009061903A8 (en) | 2010-06-24 |
WO2009061903A2 (en) | 2009-05-14 |
US20110022435A1 (en) | 2011-01-27 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US9128693B2 (en) | Systems and methods for workflow automation, adaptation and integration | |
US7835893B2 (en) | Method and system for scenario and case decision management | |
US9031823B2 (en) | Systems and methods for subsurface oil recovery optimization | |
EP2879085A1 (en) | Systems and methods for real time data management in a collaborative environment | |
WO2010101593A1 (en) | Optimizing reservoir performance under uncertainty | |
US9940414B2 (en) | Total asset modeling with integrated asset models and persistent asset models | |
US20160358271A1 (en) | Total Asset Modeling With Integrated Asset Models and Persistent Asset Models | |
Gyara et al. | Managing the production lifecycle: A framework for scalable digital oilfield implementations |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: LANDMARK GRAPHICS CORPORATION, A HALLIBURTON COMPA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:REID, LAURENCE;SZATNY, MICHAEL;JOHNSON, WILLIAM;REEL/FRAME:021851/0583;SIGNING DATES FROM 20080310 TO 20080326 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |
|
AS | Assignment |
Owner name: LANDMARK GRAPHICS CORPORATION, TEXAS Free format text: CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE PREVIOUSLY RECORDED ON REEL 021851 FRAME 0583. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT;ASSIGNORS:REID, LAURENCE;SZATNY, MICHAEL;JOHNSON, WILLIAM;REEL/FRAME:027181/0688 Effective date: 20110523 |