Schlumberger Technology Corporation

Other

Services Petroliers Schlumberger

Schlumberger Holdings Limited

Prad Research and Development Limited

Benoit Couet

William John Bailey

Kashif Rashid

Michael David Prange

Hugues A Djikpesse

David J Wilkinson

Peter Gerhard Tilke

Timothy Gareth John Jones

Michael Lynn Evans

Andrew John Carnegie

James R Hogan

Suleyman Demirel

Iain S Weir

Oliver Clinton Mullins

Terizhandur S Ramakrishnan

Tarek M Habashy

Kenneth Edward Stephenson

Robert J Schroeder

Sandip Bose

Smaine Zeroug

Bradley Albert Roscoe

Bhavani Raghuraman

Keith A Moriarty

Nikita Chugunov

Terry Wayne Stone

Jeffrey A Tarvin

Raj Banerjee

Darwin V Ellis

Joseph Ayoub

Hans Eric Klumpen

Wolfgang P Ziegler

Jeffrey Spath

Jacques M Holenka

Vladimir L'vovich Druskin

Charles R Case

Paul Albats, Jr

Richard Ian Torrens

William A Loomis

Robert Burridge

Michael Thambynayagam

William R Sloan

Scott Trevor Raphael

Gustavo Nunez

Martin Crick

Vincent Dury

Peter Kaufman

Luis C Ayestaran

Jerome A Truax

Vijaya Halabe

Françoise Allioli

Saumil Ambani

Eren Cetinkaya

Ibrahim Pamir Bursin

Stephen Flew

Michael A Elliott

Sulyman Demirel

Xing Li

Xuqing Wu

Luc Petijean

S Zema Chowdhuri

Wenyu Kong

Francedillaois Auzerais

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.

Methods and systems for calculating and evaluating value of information for reservoir fluid models derived from DFA tool data

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.

Multistage oilfield design optimization under uncertainty

Methods and systems are provided for modeling an aspect of a hydrocarbon-containing reservoir by constructing a first factor graph having variables and factors that describe the aspect of the hydrocarbon-containing reservoir. The first factor graph is converted to a tree-structured graph that does not have any cycle or loops. The tree-structured graph is converted to a second factor graph that does not contain any cycles or loops, wherein the second factor graph has variables and factors that describe the aspect of the hydrocarbon-containing reservoir. A query on the second factor graph is carried out involving message passing operations that perform probabilistic inference on the second factor graph with regard to the aspect of the hydrocarbon-containing reservoir that is modeled by the second factor graph.

Probabalistic modeling and analysis of hydrocarbon-containing reservoirs

Oilfield management includes obtaining a binary variable array describing configurable elements of an oilfield design, partitioning the binary variable array into subgroups, and applying a transformation function to each subgroup to obtain an integer variable for each subgroup. An optimization problem is solved on the binary variable array by treating the integer variable as a continuous variable to obtain a solution, and the transformation function of each subgroup is applied to the solution to obtain a design pattern. Based on the design pattern, the oilfield design is generated.

Oilfield management method and system

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.

Method of valuation of geological asset or information relating thereto in the presence of uncertainties

A method and an apparatus for managing a subterranean formation including collecting information about a flow control valve in a wellbore traversing the formation, adjusting the valve in response to the information wherein the adjusting includes a Newton method, a pattern search method, or a proxy-optimization method. In some embodiments, adjusting comprises changing the effective cross sectional area of the valve. A method and an apparatus for managing a subterranean formation including collecting information about an inflow control valve in a wellbore traversing the reservoir and controlling the valve, wherein the control includes a direct-continuous approach or a pseudo-index approach.

Method of optimization of flow control valves and inflow control devices in a single well or a group of wells

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.

Optimization with a control mechanism using a mixed-integer nonlinear formulation

Lift-gas optimization with choke control

A system for automatically optimizing a Field Development Plan (FDP) for an oil or gas field uses a fast analytic reservoir simulator to dynamically model oil or gas production from the entire reservoir over time in an accurate and rapid manner. An objective function defining a Figure of Merit (FoM) for candidate FDPs is maximized, using an optimization algorithm, to determine an optimized FDP in light of physical, engineering, operational, legal and engineering constraints. The objective function for the Figure of Merit, e.g., net present value (NPV) or total production for a given period of time, relies on a production forecast from the fast analytic reservoir simulator for the entire FDP.

Automated field development planning

A method for optimizing expensive functions with expensive nonlinear constraints. The method includes selecting sample data for evaluating an expensive function of a simulation, generating a function proxy model for the expensive function and a constraint proxy model for an expensive nonlinear constraint of the expensive function using an approximation scheme, calculating a first solution point for the simulation using the proxy models, and evaluating the expensive function at the first solution point using the sample data. When the expensive function and the proxy models do not converge at the first solution point, the method further includes adding the first solution point to the sample data for updating the proxy models. The method further includes repeating the calculation and evaluation of solution points until the expensive function and the proxy models converge and, following convergence, identifying an optimal solution of the function proxy model and the constraint proxy model.

Proxy methods for expensive function optimization with expensive nonlinear constraints

A system performs production optimization for oilfields using a mixed-integer nonlinear programming (MINLP) model. The system uses an offline-online approach to model a network of interdependent wells in an online network simulator while modeling multiple interdependent variables that control performance as an offline MINLP problem. The offline model is based on production profiles established by assuming decoupled wells in the actual network of wells. In one example, an amount of lift-gas to inject and settings for subsurface chokes are optimized. An offline solver optimizes variables through the MINLP model. Offline results are used to prime the online network simulator. Iteration between the offline and online models results in a convergence, at which point values for the interdependent variables are communicated to the real-world oilfield to optimize hydrocarbon production.

Production optimization for oilfields using a mixed-integer nonlinear programming model

A method of determining a selection of well measurements and/or their respective control parameters is described based on a global target having predetermined sensitivities to a multitude of uncertainties associated with input variables to a model including the step of ranking measurements and control parameters in accordance with their capability to reduce the uncertainties of input variables identified as most sensitive input variables through simulations using the model or a reduced variant of the model.

Method for selecting well measurements

A statistical methodology is disclosed to provide time-to-event estimates for oilfield equipment. A method according to the present invention extracts unbiased information from equipment performance data and considers parameters interactions without recourse to data thinning. The analysis explicitly accounts for items of equipment that are still operational at the time of analysis. A method according to the present invention may also be utilized to apply survival analysis to any oilfield equipment components where time-to-event information has been recorded. The method of the present invention allows comparative reckoning between different components present in the system comprising several or many individual components and allows analysis of these components either individually or simultaneously, i.e., in the presence of other components.

Statistical method for analyzing the performance of oilfield equipment

A method for performing operations of an oilfield is described. The method involves selectively coupling oilfield simulators according to a predefined configuration, each oilfield simulator modeling at least a portion of the oilfield, a first oilfield simulator receives an oilfield control parameter as an input, identifying an uncertainty parameter associated with probable values each corresponding to a weighted probability, a second oilfield simulator receives the uncertainty parameter as an input, modeling the operations of the oilfield to generate an estimated performance by selectively communicating between the oilfield simulators, the operations of the oilfield are modeled with a predetermined value of the oilfield control parameter and at least one of the probable values of the uncertainty parameter; and identifying an optimal value of the oilfield control parameter based on the estimated performance.

System and method for performing oilfield simulation operations

The invention relates to a method of performing an oilfield operation of an oilfield having at least one well having a wellbore penetrating a subterranean formation for extracting fluid from an underground reservoir therein. The method steps include analyzing the oilfield operation to generate a decision tree comprising a first decision and a second decision, wherein a first outcome of the first decision dictates acquiring information relevant to the second decision, formulating a figure of merit of the oilfield operation according to the decision tree based on the information and uncertainties associated with the oilfield, determining a value of the figure of merit by modeling the oilfield operation using statistical sampling, and performing the oilfield operation upon making the first decision based on the value of the figure of merit.

Valuing future information under uncertainty

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Belmont, MA, United States of America

Benoit Couet