A method for performing history matching of reservoir flow models using 4D seismic

Fagervik, K.; Lygren, M.; Valen, T.S.; Hetlelid, A.; Berge, Geir Thore; Dahl, Geir; Sønneland, L.; Hobbs, B. A.; Magnus, I.

doi:10.1190/1.1816429

Cited by 6 publications

(4 citation statements)

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“…Nonetheless, the full integration of quantitative 4D seismic data interpretation into the history-matching procedure is far from straightforward, remaining a challenge to be addressed as well as a topic of great interest. Several examples of quantitative approaches for integrating 4D seismic data exist in the literature (e.g., [10,[22][23][24][25][26][27][28][29][30][31]). Problems identified with the adoption of such techniques on an industrial level are related to the practical feasibility and the inexistence of a fully integrated software solution that can easily handle the integration of both production and seismic data in a computer-aided history matching loop.…”

Section: Introductionmentioning

confidence: 99%

Four-Dimensional History Matching Using ES-MDA and Flow-Based Distance-to-Front Measurement

Barrela,

Berthet,

Trani

et al. 2023

Energies

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The use of 4D seismic data in history matching has been a topic of great interest in the hydrocarbon industry as it can provide important information regarding changes in subsurfaces caused by fluid substitution and other factors where well data is not available. However, the high dimensionality and uncertainty associated with seismic data make its integration into the history-matching process a challenging task. Methods for adequate data reduction have been proposed in the past, but most address 4D information mismatch from a purely mathematical or image distance-based standpoint. In this study, we propose a quantitative and flow-based approach for integrating 4D seismic data into the history-matching process. By introducing a novel distance parametrization technique for measuring front mismatch information using streamlines, we address the problem from a flow-based standpoint; at the same time, we maintain the amount of necessary front data at a reduced and manageable amount. The proposed method is tested, and its results are compared on a synthetic case against another traditional method based on the Hausdorff distance. The effectiveness of the method is also demonstrated on a semi-synthetic model based on a real-case scenario, where the standard Hausdorff methodology could not be applied due to high data dimensionality.

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Section: Introductionmentioning

confidence: 99%

Four-Dimensional History Matching Using ES-MDA and Flow-Based Distance-to-Front Measurement

Barrela,

Berthet,

Trani

et al. 2023

Energies

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“…Several studies have been reported over the past 10 years in which quantitative approaches were investigated for incorporating the large number of data associated with seismic acquisition into existing workflows for assisted history matching of production data (e.g., Arenas et al 2001;Fagervik et al 2001;Gosselin et al 2001;van Ditzhuijzen et al 2001;Dong and Oliver 2005;Haverl et al 2005;Portella and Emerick 2005;Stephen et al 2006;Dadashpour et al 2007;Roggero et al 2007). For computational reasons, the workflow used in most of these studies requires significant reduction of the uncertainty space, or they produce only a single history-matched model.…”

Section: Introductionmentioning

confidence: 99%

Seismic History Matching of Fluid Fronts Using the Ensemble Kalman Filter

Trani

Arts²,

Leeuwenburgh³

2012

SPE Journal

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Time-lapse seismic data provide information on the dynamics of multiphase reservoir fluid flow in places where no production data from wells are available. This information, in principle, could be used to estimate unknown reservoir properties. However, the amount, resolution, and character of the data have long posed significant challenges for quantitative use in assisted-historymatching workflows. Previous studies, therefore, have generally investigated methods for updating single models with reduced parameter-uncertainty space. Recent developments in ensemblebased history-matching methods have shown the feasibility of multimodel history and matching of production data while maintaining a full uncertainty description. Here, we introduce a robust and flexible reparameterization for interpreted fluid fronts or seismic attribute isolines that extends these developments to seismic history matching. The seismic data set is reparameterized, in terms of arrival times, at observed front positions, thereby significantly reducing the number of data while retaining essential information. A simple 1D example is used to introduce the concepts of the approach. A synthetic 3D example, with spatial complexity that is typical for many waterfloods, is examined in detail. History-matching cases based on both separate and combined use of production and seismic data are examined. It is shown that consistent multimodel history matches can be obtained without the need for reduction of the parameter space or for localization of the impact of observations. The quality of forecasts based on the history-matched models is evaluated by simulating both expected production and saturation changes throughout the field for a fixed operating strategy. It is shown that bias and uncertainty in the forecasts of production both at existing wells and in the flooded area are reduced considerably when both production and seismic data are incorporated. The proposed workflow, therefore, enables better decisions on field developments that require optimal placement of infill wells.

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“…These involve computation of a misfit between predicted and observed data and then a mathematical routine is used to choose new models either stochastically or deterministically. Many researchers have investigated different inversion algorithms, parameterization schemes and appropriate methods to compare data (Huang et al 1997;Gosselin et al 2001;Aanonsen et al 2001;Arenas et al 2001;Fagervik et al 2001;Kretz et al 2001;Mantica et al 2001;Vasco et al 2001;Portella and Emerick 2005;Jin et al 2007;Roggero et al 2007;Skjervheim et al 2007). Often observed acoustic impedance changes, which may be of undefined units, are compared to equivalent synthetic seismic data (Guerillot and Pianelo 2000;Clifford et al 2003;Mezghani, et al 2004;Emerick et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Seismic History Matching of Nelson using Time-lapse Seismic Data: An Investigation of 4D Signature Normalization

Kazemi¹,

Stephen²,

Shams³

2010

All Days

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History matching of a reservoir model is always a difficult task. In some fields we can use time-lapse (4D) seismic data to detect production induced changes as a complement to more conventional production data. In seismic history matching we predict these data and compare to observations. Observed time-lapse data often consists of relative measures of change which requires normalization. We investigate different normalization approaches, based on predicted 4D data, and assess their impact on history matching.We apply the approach to the Nelson field in which four surveys are available over nine years of production. We normalize the 4D signature in a number of ways. Firstly we use predictions of 4D signature from vertical wells that match production and derive a normalization function. As an alternative, we use cross-plots of the full field prediction against observation. Normalized observations are used in an automatic history matching process where the model is updated. We analyse the results of the two normalization approaches and compare against the case of just using production data.The result shows that when we use 4D data normalized to wells, we obtain 49% reduced misfit along with 36% improvement in predictions. Also over the whole reservoir, 8% and 7% reduction of misfits for 4D seismic are obtained in history and prediction periods respectively. When we use only production data the production history match is improved to a similar degree (45%) but in predictions, the improvement is only 25% and the 4D seismic misfit is ten percent worse.Finding the unswept areas in the reservoir is always a challenge in reservoir management. By using 4D data in history matching we can better predict reservoir behaviour and identify regions of remaining oil.

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A method for performing history matching of reservoir flow models using 4D seismic

Cited by 6 publications

References 0 publications

Four-Dimensional History Matching Using ES-MDA and Flow-Based Distance-to-Front Measurement

Four-Dimensional History Matching Using ES-MDA and Flow-Based Distance-to-Front Measurement

Seismic History Matching of Fluid Fronts Using the Ensemble Kalman Filter

Seismic History Matching of Nelson using Time-lapse Seismic Data: An Investigation of 4D Signature Normalization

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