US20140019108A1 - Method for exploiting a geological reservoir from a reservoir model matched by the computation of an analytical law of conditional distribution of uncertain parameters of the model - Google Patents

Method for exploiting a geological reservoir from a reservoir model matched by the computation of an analytical law of conditional distribution of uncertain parameters of the model Download PDF

Info

Publication number
US20140019108A1
US20140019108A1 US13/930,239 US201313930239A US2014019108A1 US 20140019108 A1 US20140019108 A1 US 20140019108A1 US 201313930239 A US201313930239 A US 201313930239A US 2014019108 A1 US2014019108 A1 US 2014019108A1
Authority
US
United States
Prior art keywords
reservoir
models
parameters
model
objective function
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
Application number
US13/930,239
Other languages
English (en)
Inventor
Sebastien Da Veiga
Veronique Gervais-Couplet
Mathieu Feraille
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
IFP Energies Nouvelles IFPEN
Original Assignee
IFP Energies Nouvelles IFPEN
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by IFP Energies Nouvelles IFPEN filed Critical IFP Energies Nouvelles IFPEN
Assigned to IFP Energies Nouvelles reassignment IFP Energies Nouvelles ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: GERVAIS-COUPLET, VERONIQUE, DA VEIGA, SEBASTIEN, FERAILLE, MATHIEU
Publication of US20140019108A1 publication Critical patent/US20140019108A1/en
Abandoned legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V20/00—Geomodelling in general
    • E21B41/0092—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B41/00—Equipment or details not covered by groups E21B15/00 - E21B40/00
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B2200/00—Special features related to earth drilling for obtaining oil, gas or water
    • E21B2200/20—Computer models or simulations, e.g. for reservoirs under production, drill bits

Definitions

  • a reservoir model constitutes an experimental model of the subsoil, representative of its structure and of its behavior.
  • this type of experimental model is represented on a computer, and it is then called a numerical model.
  • a reservoir model comprises a mesh, or grid, generally three-dimensional, associated with one or more maps of petrophysical properties (porosity, permeability, saturation, etc.). The association assigns values of the geophysical properties to each of the mesh cells of the grid.
  • History matching modifies the parameters of a reservoir model, such as the permeabilities, the porosities or the skins of wells (representing damage around the well), fault connections, etc., to minimize the deviations between the measured history data and the corresponding responses simulated on the basis of the reservoir model.
  • the parameters may be linked to geographic regions like the permeabilities or porosities around one or several wells.
  • the deviation between the history data and simulated responses forms a functional, called the objective function.
  • the history-matching problem is solved by minimizing this functional.
  • an objective function F( ⁇ ) is determined that measures a deviation between dynamic data y 1 , . . . , y n acquired during exploitation and dynamic data simulated by a flow simultator and the reservoir models belonging to the set;
  • y 1 , . . . , y n ) of conditional probability of the parameters ⁇ is determined from the knowledge of measured dynamic data y 1 , . . . , y n ;
  • the M 1 models added to the set are chosen using the approximation of the function G( ⁇ ).
  • FIG. 1 illustrates the method for exploiting an oil reservoir according to the invention.
  • the method comprises the following main steps:
  • an initial set of reservoir models is generated stochastically by the a priori law of probability p( ⁇ ) of each uncertain parameter.
  • a flow simulator f is used to compute the production response simulated with the reservoir models that are to be assessed (SIM);
  • the probabilistic matching is carried out with an initial experimental design of latin hypercube type LHS defining a set made up of 70 reservoir models, then with an addition of models in series of 10 at each iteration of the matching process.
  • the first 5 models added are chosen at the point where the response surface ⁇ tilde over (G) ⁇ ( ⁇ ) predicts large values, and the next 5 where the quality of the approximation of G( ⁇ ) is low in terms of high kriging variance.
  • the trend of the objective function during the procedure for adding models in the process of matching of the numerical model of the reservoir is given in FIG. 2 .
  • the darkest vertical bars mark the last simulation of the LHS and of each model addition series. It can then be seen that, after the first 70 exploration models (LHS), the points added in series of 10 indeed exhibit 5 first globally low values of the objective function, then 5 globally higher values.
  • conditional law of distribution is determined on the basis of the results of the step 3, that are compared to the exact a posteriori laws.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Fluid Mechanics (AREA)
  • General Engineering & Computer Science (AREA)
  • Geometry (AREA)
  • Geology (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • Mathematical Physics (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • Computing Systems (AREA)
  • Geophysics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mining & Mineral Resources (AREA)
  • Algebra (AREA)
  • Geochemistry & Mineralogy (AREA)
  • Environmental & Geological Engineering (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Operations Research (AREA)
  • Sampling And Sample Adjustment (AREA)
US13/930,239 2012-07-13 2013-06-28 Method for exploiting a geological reservoir from a reservoir model matched by the computation of an analytical law of conditional distribution of uncertain parameters of the model Abandoned US20140019108A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR1202005A FR2993310B1 (fr) 2012-07-13 2012-07-13 Procede d'exploitation d'un reservoir geologique a partir d'un modele de reservoir cale par le calcul d'une loi analytique de distribution conditionnelle de parametres incertains du modele
FR12/02005 2012-07-13

Publications (1)

Publication Number Publication Date
US20140019108A1 true US20140019108A1 (en) 2014-01-16

Family

ID=47227856

Family Applications (1)

Application Number Title Priority Date Filing Date
US13/930,239 Abandoned US20140019108A1 (en) 2012-07-13 2013-06-28 Method for exploiting a geological reservoir from a reservoir model matched by the computation of an analytical law of conditional distribution of uncertain parameters of the model

Country Status (4)

Country Link
US (1) US20140019108A1 (fr)
EP (1) EP2685291B1 (fr)
CA (1) CA2821099C (fr)
FR (1) FR2993310B1 (fr)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017112033A1 (fr) * 2015-12-22 2017-06-29 Chevron U.S.A. Inc. Méthodologie pour construire des modèles stratigraphiques prospectifs numériques réalistes dans un environnement de données éparses
US10393923B2 (en) * 2014-05-19 2019-08-27 Total Sa Method of determining a map of height of liquid hydrocarbon in a reservoir
CN113240181A (zh) * 2021-05-19 2021-08-10 华中科技大学 一种水库调度运行滚动模拟方法及装置
US11268352B2 (en) * 2019-04-01 2022-03-08 Saudi Arabian Oil Company Controlling fluid volume variations of a reservoir under production
US11460595B2 (en) 2019-04-18 2022-10-04 Saudi Arabian Oil Company Unified continuous seismic reservoir monitoring
RU2783031C1 (ru) * 2022-01-31 2022-11-08 Публичное акционерное общество "Нефтяная компания "Роснефть" (ПАО "НК "Роснефть") Способ разработки нефтяной залежи
CN116464437A (zh) * 2023-04-23 2023-07-21 西南石油大学 一种碳酸盐岩气藏地层水产水量的预测方法

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113655521B (zh) * 2021-07-13 2022-06-14 华南理工大学 基于离散拉丁超立方抽样选波方法

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030028325A1 (en) * 2001-04-19 2003-02-06 Frederic Roggero Method of constraining by dynamic production data a fine model representative of the distribution in the reservoir of a physical quantity characteristic of the subsoil structure
US20080162100A1 (en) * 2006-12-28 2008-07-03 Chevron U.S.A. Inc. Method, system and program storage device for history matching and forecasting of hydrocarbon-bearing reservoirs utilizing proxies for likelihood functions
US20090043555A1 (en) * 2007-08-06 2009-02-12 Daniel Busby Method for Evaluating an Underground Reservoir Production Scheme Taking Account of Uncertainties
US20090198447A1 (en) * 2008-02-06 2009-08-06 Emmanuel Legendre System and method for displaying data associated with subsurface reservoirs
US20110153285A1 (en) * 2009-12-23 2011-06-23 Da Veiga Sebastien Method of developing a petroleum reservoir from a facies map construction
US20120095733A1 (en) * 2010-06-02 2012-04-19 Schlumberger Technology Corporation Methods, systems, apparatuses, and computer-readable mediums for integrated production optimization
US20120232865A1 (en) * 2009-09-25 2012-09-13 Landmark Graphics Corporation Systems and Methods for the Quantitative Estimate of Production-Forecast Uncertainty

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8335677B2 (en) * 2006-09-01 2012-12-18 Chevron U.S.A. Inc. Method for history matching and uncertainty quantification assisted by global optimization techniques utilizing proxies

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030028325A1 (en) * 2001-04-19 2003-02-06 Frederic Roggero Method of constraining by dynamic production data a fine model representative of the distribution in the reservoir of a physical quantity characteristic of the subsoil structure
US20080162100A1 (en) * 2006-12-28 2008-07-03 Chevron U.S.A. Inc. Method, system and program storage device for history matching and forecasting of hydrocarbon-bearing reservoirs utilizing proxies for likelihood functions
US20090043555A1 (en) * 2007-08-06 2009-02-12 Daniel Busby Method for Evaluating an Underground Reservoir Production Scheme Taking Account of Uncertainties
US20090198447A1 (en) * 2008-02-06 2009-08-06 Emmanuel Legendre System and method for displaying data associated with subsurface reservoirs
US20120232865A1 (en) * 2009-09-25 2012-09-13 Landmark Graphics Corporation Systems and Methods for the Quantitative Estimate of Production-Forecast Uncertainty
US20110153285A1 (en) * 2009-12-23 2011-06-23 Da Veiga Sebastien Method of developing a petroleum reservoir from a facies map construction
US20120095733A1 (en) * 2010-06-02 2012-04-19 Schlumberger Technology Corporation Methods, systems, apparatuses, and computer-readable mediums for integrated production optimization

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
DANIEL BUSBY, SEBASTIEN DA VEIGA, SAMIR TOUZANI, A workflow for decision making under uncertainty, Comput Geosci (2014) 18:519–533 *
GERVAIS-COUPLET, V., ROGGERO, F., FERAILLE, M. D., LE RAVALEC-DUPIN, M., & SEILER, A. Joint History Matching of Production and 4D-Seismic Related Data for a North Sea Field Case. Society of Petroleum Engineers. (2010, January 1) doi:10.2118/135116-MS *
JAN-ARILD SKJERVHEIM, Continuous Updating of a Coupled Reservoir-Seismic Model Using an Ensemble Kalman Filter Technique, PhD Thesis, University of Bergen, 2007, 224 pages *
M. FERAILLE, D. BUSBY, Uncertainty Management on a Reservoir Workflow, International Petroleum Technology Conference held in Doha, Qatar, 7- 9 December 2009, 16 pages *
MATHIEU FERAILLE AND FREDERIC ROGGERO, Uncertainty Quantification for Mature Field Combining the Bayesian Inversion Formalism and Experimental Design Approach, 9th European Conference on the Mathematics of Oil Recovery — Cannes, France, 30 August - 2 September 2004, 8 pages *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10393923B2 (en) * 2014-05-19 2019-08-27 Total Sa Method of determining a map of height of liquid hydrocarbon in a reservoir
WO2017112033A1 (fr) * 2015-12-22 2017-06-29 Chevron U.S.A. Inc. Méthodologie pour construire des modèles stratigraphiques prospectifs numériques réalistes dans un environnement de données éparses
US11268352B2 (en) * 2019-04-01 2022-03-08 Saudi Arabian Oil Company Controlling fluid volume variations of a reservoir under production
US11460595B2 (en) 2019-04-18 2022-10-04 Saudi Arabian Oil Company Unified continuous seismic reservoir monitoring
CN113240181A (zh) * 2021-05-19 2021-08-10 华中科技大学 一种水库调度运行滚动模拟方法及装置
RU2783031C1 (ru) * 2022-01-31 2022-11-08 Публичное акционерное общество "Нефтяная компания "Роснефть" (ПАО "НК "Роснефть") Способ разработки нефтяной залежи
CN116464437A (zh) * 2023-04-23 2023-07-21 西南石油大学 一种碳酸盐岩气藏地层水产水量的预测方法
US20240354787A1 (en) * 2023-04-23 2024-10-24 Southwest Petroleum University Prediction method for formation water yield of carbonate gas reservo

Also Published As

Publication number Publication date
CA2821099C (fr) 2020-05-12
EP2685291A3 (fr) 2016-12-14
EP2685291A2 (fr) 2014-01-15
EP2685291B1 (fr) 2022-03-09
FR2993310A1 (fr) 2014-01-17
FR2993310B1 (fr) 2014-08-29
CA2821099A1 (fr) 2014-01-13

Similar Documents

Publication Publication Date Title
CA3043756C (fr) Procede et systeme de regression et de classification dans des modeles de subsurface pour supporter la prise de decisions dans les operations d'exploitation d'hydrocarbures
US8392164B2 (en) Method for evaluating an underground reservoir production scheme taking account of uncertainties
US9805144B2 (en) Method for exploiting a geological reservoir on the basis of a reservoir model matched by means of multiple-scale parameterization
US20140019108A1 (en) Method for exploiting a geological reservoir from a reservoir model matched by the computation of an analytical law of conditional distribution of uncertain parameters of the model
US8868390B2 (en) Method of developing a petroleum reservoir from a flow model calibrated through pressure and saturation map scaling
Bianco et al. History matching and production forecast uncertainty by means of the ensemble Kalman filter: A real field application
US8874419B2 (en) Method of developing a petroleum reservoir from a facies map construction
US9135378B2 (en) Method of developing a reservoir from a technique of selecting the positions of wells to be drilled
US8818781B2 (en) Method for operating an oil pool based on a reservoir model gradually deformed by means of cosimulations
US8965744B2 (en) Method of developing a petroleum reservoir by reservoir model reconstruction
Siade et al. A practical, robust methodology for acquiring new observation data using computationally expensive groundwater models
Xu et al. Inverse sequential simulation: A new approach for the characterization of hydraulic conductivities demonstrated on a non‐G aussian field
US8942967B2 (en) Method for real-time reservoir model updating from dynamic data while keeping the coherence thereof with static observations
Juda et al. A framework for the cross‐validation of categorical geostatistical simulations
EP2770162B1 (fr) Procédé d'exploitation d'un réservoir géologique au moyen d'un modèle de réservoir calé et cohérent vis à vis des propriétés d'écoulement
WO2020142257A1 (fr) Procédé et système d'évaluation de variabilité dans des modèles de subsurface pour supporter la prise de décisions dans des exploitations d'hydrocarbures
Pyrcz et al. Uncertainty in reservoir modeling
US9187985B2 (en) Method for optimizing the development of an underground medium by means of a reservoir study comprising optimized upscaling
Fang et al. Data-driven model falsification and uncertainty quantification for fractured reservoirs
Athens et al. Gravity inversion for geothermal exploration with uncertainty quantification
Lam et al. Multiresolution approach to condition categorical multiple‐point realizations to dynamic data with iterative ensemble smoothing
Limbeck et al. Using machine learning for model benchmarking and forecasting of depletion-induced seismicity in the Groningen gas field
Bazargan An efficient polynomial chaos-based proxy model for history matching and uncertainty quantification of complex geological structures
Jo et al. Sensitivity analysis of geological rule-based subsurface model parameters on fluid flow
US20230417949A1 (en) Method for determining uncertainties associated with a model of a sedimentary basin

Legal Events

Date Code Title Description
AS Assignment

Owner name: IFP ENERGIES NOUVELLES, FRANCE

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:DA VEIGA, SEBASTIEN;GERVAIS-COUPLET, VERONIQUE;FERAILLE, MATHIEU;SIGNING DATES FROM 20130718 TO 20130724;REEL/FRAME:031106/0839

STPP Information on status: patent application and granting procedure in general

Free format text: RESPONSE TO NON-FINAL OFFICE ACTION ENTERED AND FORWARDED TO EXAMINER

STPP Information on status: patent application and granting procedure in general

Free format text: FINAL REJECTION MAILED

STPP Information on status: patent application and granting procedure in general

Free format text: RESPONSE AFTER FINAL ACTION FORWARDED TO EXAMINER

STPP Information on status: patent application and granting procedure in general

Free format text: ADVISORY ACTION MAILED

STPP Information on status: patent application and granting procedure in general

Free format text: DOCKETED NEW CASE - READY FOR EXAMINATION

STPP Information on status: patent application and granting procedure in general

Free format text: NON FINAL ACTION MAILED

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION