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    Multistage Oilfield Design Optimization Under Uncertainty
    2.
    发明申请
    Multistage Oilfield Design Optimization Under Uncertainty 审中-公开
    不确定性下多级油田设计优化

    公开(公告)号：US20160326845A1

    公开(公告)日：2016-11-10

    申请号：US15109671

    申请日：2015-01-06

    Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION

    Inventor： Hugues A. Djikpesse ,  Kashif Rashid ,  William J. Bailey ,  Michael David Prange ,  Benoit Couet

    IPC: E21B41/00 ,  G06F17/50 ,  E21B43/26 ,  E21B43/267 ,  E21B47/00 ,  E21B49/00

    Abstract: Managing oilfield operations include obtaining a subsurface model including a fracture design model having an fracture property with an uncertain value. A set of representative values that represent uncertainty in the fracture property is obtained and used to solve an oilfield optimization problem with a control variable to obtain a solution. The solution includes an optimal value for the control variable. Based on the solution, an oilfield design is generated and stored.

    Abstract translation: 管理油田作业包括获得地下模型，包括具有不确定值的断裂特性的断裂设计模型。 获得代表断裂性质不确定性的一组代表性值，并用于解决具有控制变量的油田优化问题以获得解决方案。 该解决方案包含控制变量的最优值。 基于该解决方案，生成并存储油田设计。

    Method of valuation of geological asset or information relating thereto in the presence of uncertainties
    3.
    发明授权
    Method of valuation of geological asset or information relating thereto in the presence of uncertainties 有权

    公开(公告)号：US10430872B2

    公开(公告)日：2019-10-01

    申请号：US13784666

    申请日：2013-03-04

    Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION

    Inventor： David J. Wilkinson ,  Nikita Chugunov ,  William J. Bailey ,  Benoit Couet ,  Terizhandur S. Ramakrishnan

    IPC: G06Q40/00 ,  G06Q10/06

    Abstract: Methods are disclosed for assigning a value to a geological asset or information relating thereto in the presence of private and public sources of uncertainties. The private and public uncertainties associated with a geological asset or information associated therewith are defined, and private uncertainties are assigned a subjective probability representing the best state of knowledge currently available. A multi-dimensional valuation-time lattice is constructed using the subjective probabilities for the private uncertainties and using risk-neutral probabilities for the public uncertainties. A backward recursion through the multi-dimensional lattice is performed in order to generate a present value for the asset given the present information available. During the backward recursion, a tally of delta hedging coefficients is generated and stored in order to provide an operational “map” or “decision pathway” should the project move forward.

    Methods and Systems for Calculating and Evaluating Value of Information for Reservoir Fluid Models Derived from DFA Tool Data
    5.
    发明申请
    Methods and Systems for Calculating and Evaluating Value of Information for Reservoir Fluid Models Derived from DFA Tool Data 审中-公开
    用于计算和评估DFA工具数据的储层流体模型信息值的方法和系统

    公开(公告)号：US20150363520A1

    公开(公告)日：2015-12-17

    申请号：US14762828

    申请日：2014-01-13

    Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION

    Inventor： William J. Bailey ,  Benoit Couet ,  Peter Kaufman ,  Oliver C. Mullins

    IPC: G06F17/50 ,  E21B49/08

    CPC classification number: G01V99/005 ,  E21B49/00 ,  E21B49/08 ,  E21B49/087 ,  E21B49/10 ,  G01V11/00

    Abstract: A method for deriving VOI for a hydrocarbon-bearing reservoir fluid model based on DFA data (“true fluid model”) versus an “incorrect fluid model” includes calculating first, second and third objective functions that are based on NPV(s) of simulated production by a reservoir simulator with different configurations. For the first objective function, the simulator is configured with the incorrect fluid model and control variables that are optimized to derive a first group of control variable values. For the second objective function, the simulator is configured with the true fluid model and the first group of control variable values. For the third objective function, the simulator is configured with the true fluid model and control variables that are optimized to identify a second group of control variable values. The objective functions can be deterministic, or can include statistics that account for uncertainty. A visualization of such results with uncertainty is also described.

    Abstract translation: 基于DFA数据（“真实流体模型”）与“不正确的流体模型”相比，用于导出含烃储层流体模型的VOI的方法包括计算基于模拟的NPV的第一，第二和第三目标函数 通过不同配置的油藏模拟器生产。 对于第一个目标函数，模拟器配置有不正确的流体模型和被优化以得到第一组控制变量值的控制变量。 对于第二个目标函数，模拟器配置有真实流体模型和第一组控制变量值。 对于第三目标函数，模拟器配置有真实的流体模型和被优化以识别第二组控制变量值的控制变量。 目标函数可以是确定性的，也可以包括考虑不确定性的统计学。 还描述了具有不确定性的这种结果的可视化。

    Methods and systems for calculating and evaluating value of information for reservoir fluid models derived from DFA tool data
    6.
    发明授权
    Methods and systems for calculating and evaluating value of information for reservoir fluid models derived from DFA tool data 有权

    公开(公告)号：US10989835B2

    公开(公告)日：2021-04-27

    申请号：US14762828

    申请日：2014-01-13

    Applicant: Schlumberger Technology Corporation

    Inventor： William J. Bailey ,  Benoit Couet ,  Peter Kaufman ,  Oliver C. Mullins

    IPC: E21B49/08 ,  G01V99/00 ,  G01V11/00 ,  E21B49/10 ,  E21B49/00

    Abstract: A method for deriving VOI for a hydrocarbon-bearing reservoir fluid model based on DFA data (“true fluid model”) versus an “incorrect fluid model” includes calculating first, second and third objective functions that are based on NPV(s) of simulated production by a reservoir simulator with different configurations. For the first objective function, the simulator is configured with the incorrect fluid model and control variables that are optimized to derive a first group of control variable values. For the second objective function, the simulator is configured with the true fluid model and the first group of control variable values. For the third objective function, the simulator is configured with the true fluid model and control variables that are optimized to identify a second group of control variable values. The objective functions can be deterministic, or can include statistics that account for uncertainty. A visualization of such results with uncertainty is also described.

    AUTOMATED SURFACE NETWORK GENERATION
    8.
    发明申请
    AUTOMATED SURFACE NETWORK GENERATION 审中-公开
    自动表面网络生成

    公开(公告)号：US20150339411A1

    公开(公告)日：2015-11-26

    申请号：US14285014

    申请日：2014-05-22

    Applicant: Schlumberger Technology Corporation

    Inventor： Scott Trevor Raphael ,  Benoit Couet ,  William J. Bailey ,  Kashif Rashid ,  Peter Gerhard Tilke

    IPC: G06F17/50 ,  G06F17/18

    CPC classification number: G06F17/50 ,  E21B43/30 ,  G06F17/18 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q50/02

    Abstract: A method, apparatus, and program product automatically generate a surface network for an oilfield production system, e.g., as a new surface network or as an addition to an existing surface network. Candidate surface networks are generated from control vectors proposed by an optimization engine to optimize based upon an objective function that is based at least upon one or more geographical cost functions and one or more boundary conditions.

    Abstract translation: 方法，装置和程序产品自动生成用于油田生产系统的表面网络，例如作为新的表面网络或作为对现有表面网络的补充。 候选表面网络由优化引擎提出的控制向量生成，以基于至少基于一个或多个地理成本函数和一个或多个边界条件的目标函数进行优化。

    OPTIMIZATION WITH A CONTROL MECHANISM USING A MIXED-INTEGER NONLINEAR FORMULATION
    10.
    发明申请
    OPTIMIZATION WITH A CONTROL MECHANISM USING A MIXED-INTEGER NONLINEAR FORMULATION 审中-公开
    使用混合整数非线性公式优化控制机制

    公开(公告)号：US20140156238A1

    公开(公告)日：2014-06-05

    申请号：US14174643

    申请日：2014-02-06

    Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION

    Inventor： Kashif Rashid ,  Sulyman Demirel ,  Benoit Couet

    IPC: G06F17/50

    CPC classification number: G06F17/5009 ,  E21B41/0035 ,  E21B41/0092 ,  E21B43/00 ,  E21B43/12 ,  E21B43/122 ,  E21B43/14 ,  E21B44/00 ,  E21B2041/0028 ,  G05B13/04 ,  G05B15/00 ,  G05B17/00

    Abstract: A method of optimizing production of wells using choke control includes generating, for each well, an intermediate solution to optimize the production of each well. The generating includes using an offline model that includes a mixed-integer nonlinear program solver and includes using production curves based on a choke state and a given wellhead pressure. The method further includes calculating, using a network model and the intermediate solution of each well, a current online wellhead pressure for each well. The method further includes setting the intermediate solution as a final solution based on determining that a difference between the current online wellhead pressure of each well and a prior online wellhead pressure of each well is less than a tolerance amount. The method further includes adjusting, using the final solution of each well, at least one operating parameter of the wells.

    Abstract translation: 使用扼流器控制来优化井的生产的方法包括为每个井生成中间溶液以优化每个井的产量。 该生成包括使用包括混合整数非线性程序求解器的离线模型，并且包括使用基于阻塞状态和给定井口压力的生产曲线。 该方法还包括使用每个井的网络模型和中间解决方案来计算每个井的当前在线井口压力。 该方法还包括基于确定每个井的当前在线井口压力和每个井的先前在线井口压力之间的差小于公差量，将中间解决方案设置为最终解决方案。 该方法还包括使用每个井的最终解决方案来调节井的至少一个操作参数。

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