History Matching of Production and 4D Seismic Data: Application to the Girassol Field, Offshore Angola

Roggero, F.; Lerat, Olivier; Ding, Didier Yu; Berthet, Philippe; Bordenave, Claude; Lefeuvre, F.; Perfetti, Pierre

doi:10.2516/ogst/2011148

Cited by 35 publications

(17 citation statements)

References 34 publications

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“…There is substantial work in the open literature on the integration of production and time-lapse seismic data for improving reservoir characterization and history-matching (Huang et al, 1997;Kretz et al, 2002;Waggoner et al, 2003;Gosselin et al, 2003;Stephen et al, 2006;Roggero et al, 2007;Emerick et al, 2007;Dong and Oliver, 2008;Dadashpour et al, 2010;Landa and Kumar, 2011). The time-lapse seismic data can be integrated on different levels, which may be time-lapse changes of impedance, saturation, Poisson's ratio, zero-offset amplitude and amplitude versus offset (AVO) gradient, or seismic amplitude traces.…”

Section: Introductionmentioning

confidence: 98%

Simultaneous estimation of permeability and porosity from joint inversion of time-lapse seismic, electromagnetic, and production data

Liang

Abubakar

Habashy

2013

SEG Technical Program Expanded Abstracts 2013

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We present an approach for the simultaneous estimation of permeability and porosity from time-lapse seismic, time-lapse electromagnetic, and production data. Permeability and porosity are some of the most important parameters for reservoir characterization because of their significant influence over oil recovery. Both permeability and porosity has a big footprint on the distribution of saturation and pressure in the reservoir during production, which can be snapshot by the time-lapse seismic and time-lapse electromagnetic measurements. Production data is the traditional source used for reservoir model conditioning but only provides limited constraint to the reservoir model that is very localized to the near-wellbore regions. In contrast, time-lapse seismic and time-lapse electromagnetic can impose additional constraints to the reservoir model conditioning problem covering the inter-well regions. We have developed a reservoir centric workflow to allow jointly invert these multiphysical data. The non-uniqueness of this inverse problem is hence effectively reduced. We use a synthetic case to demonstrate that the proposed approach can significantly improve the estimation of permeability and porosity as well as the fluid-front movement monitoring.

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Section: Introductionmentioning

confidence: 98%

Simultaneous estimation of permeability and porosity from joint inversion of time-lapse seismic, electromagnetic, and production data

Liang

Abubakar

Habashy

2013

SEG Technical Program Expanded Abstracts 2013

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“…Recent studies on real field cases such as the one performed on the Girassol field [21] highlighted the difficulty to match seismic data in assisted history matching processes. This result stressed the need to use the information provided by seismic data to define adapted parameterization techniques.…”

Section: Introductionmentioning

confidence: 99%

“…Let us note that conditional kriging on data with volume support can also be applied to indicator functions to perturb facies proportions as proposed in [22]. These techniques were applied to match 4D seismic-related data in real-field cases [21] and synthetic cases [10,15,17] for instance. The choice of the spatial supports associated to the perturbed parameters (deformation parameters, pilot points, or blocks) was driven by the error on seismic data.…”

Section: Introductionmentioning

confidence: 99%

Local adaptive parameterization for the history matching of 3D seismic data

Veiga

Gervais

2011

Comput Geosci

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Matching seismic data in assisted history matching processes can be a challenging task. One main idea is to bring flexibility in the choice of the parameters to be perturbed, focusing on the information provided by seismic data. Local parameterization techniques such as pilot-point or gradual deformation methods can be introduced, considering their high adaptability. However, the choice of the spatial supports associated to the perturbed parameters is crucial to successfully reduce the seismic mismatch. The information related to seismic data is sometimes considered to initialize such local methods. Recent attempts to define the regions adaptively have been proposed, focusing on the mismatch between simulated and reference seismic data. However, the regions are defined manually for each optimization process. Therefore, we propose to drive the definition of the parameter support by performing an automatic definition of the regions to be perturbed from the residual maps related to the 3D seismic data. Two methods are developed in this paper. The first one consists in clustering the residual map with classification algorithms. The second method proposes to drive the generation of pilot point locations in an adaptive way. Residual maps, after proper normalization, are considered as probability density functions of the pilot point locations. Both procedures lead to a complete adaptive and highly flexible perturbation technique for 3D seismic matching. A synthetic study based on the PUNQ test case is introduced to illustrate the potential of these adaptive strategies.

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“…Assisted history matching has been widely used in petroleum engineering to constrain reservoir and/or geological models by integrating well production data and/or 4D seismic data (see for example, Chavent et al 1975;Bissell et al 1994;Chu et al 1995;Landa and Horne 1997;Roggero et al 1998Roggero et al , 2007Gosselin et al 2000). History matching is a complex inverse problem for which the degree of difficulty and the computational effort (in terms of the number of reservoir simulations, which are very expensive in CPU time) increase with the increasing of the number of matching parameters.…”

Section: Introductionmentioning

confidence: 99%

Development of a Data Partition Technique for Gradient-Based Optimization Methods in History Matching

Ding¹

2010

SPE EUROPEC/EAGE Annual Conference and Exhibition

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Assisted history matching is now widely used to constrain reservoir models. However, history matching is a complex inverse problem, and it is always a big challenge to history match large fields with a large number of parameters.In this paper, we present a new technique for the gradient-based optimization methods to improve history matching for large fields. This new technique is based on data partition for the gradient calculations. The objective function is first split into local components, and the dependence of each local component on principal parameters is then analyzed to minimize the number of influential parameters. The interaction between parameters and local components is allowed in the splitting. Based on this study, we can propose a perturbation design, which allows us to calculate all derivatives of the objective function with only a few perturbations. This method is particularly interesting for regional and well level history matching, and it is also suitable to match geostatistical models by introducing numerous local parameters. This new technique makes history matching with a large number of parameters (large field) tractable. IntroductionAssisted history matching has been widely used in petroleum engineering to constrain reservoir and/or geological models by integrating well production data and/or 4D seismic data (see for example, Chavent et al. 1975;Bissell et al. 1994;Chu et al. 1995;Landa and Horne 1997;Roggero et al. 1998Roggero et al. , 2007Gosselin et al. 2000). History matching is a complex inverse problem for which the degree of difficulty and the computational effort (in terms of the number of reservoir simulations, which are very expensive in CPU time) increase with the increasing of the number of matching parameters. The general strategy of history matching is to start at the field level and work down to more detailed matching. A reasonable match is first at the field level, then at the regional level, followed by more rigorous individual well history matching. The number of parameters is generally increased when the history matching gets down to the regional or well levels. So, it is important to study optimization methodologies for a large number of parameters, and especially for large fields.Among the optimization methods for history matching, the gradient-based approaches are often used (see for example, Chavent et al. 1975;Gosselin et al. 2000; Olivier et al. 2008). However, the gradients of the objective function are generally calculated by numerical methods, which need the evaluation of the objective function through reservoir simulations, which, in turn, are very expensive in CPU time. If we want to optimize M parameters, we require at least M perturbations (M+1 simulations) to calculate all the gradients in order to obtain an optimized solution. When the number of parameters M is large, we may encounter serious problems in CPU time for optimizations in history matching.Adjoint method is an efficient technique to reduce the number of simulations for the gradient calculation (...

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History Matching of Production and 4D Seismic Data: Application to the Girassol Field, Offshore Angola

Cited by 35 publications

References 34 publications

Simultaneous estimation of permeability and porosity from joint inversion of time-lapse seismic, electromagnetic, and production data

Simultaneous estimation of permeability and porosity from joint inversion of time-lapse seismic, electromagnetic, and production data

Local adaptive parameterization for the history matching of 3D seismic data

Development of a Data Partition Technique for Gradient-Based Optimization Methods in History Matching

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