Joint inversion of controlled-source electromagnetic and production data for reservoir monitoring

Liang, Lin; Abubakar, Aria; Habashy, Tarek M.

doi:10.1190/geo2012-0013.1

Cited by 7 publications

(3 citation statements)

References 36 publications

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“…Some of these studies are based on synthetic models of existing producing hydrocarbon fields (Ziolkowski et al 2010;Black et al 2011;Colombo & McNeice 2013;Zerilli et al 2018). Some studies use reservoir simulations to demonstrate that CSEM data can be directly linked to monitoring changes in the fluid saturation and motion of the flooding front (Ziolkowski et al 2010;Liang et al 2012;Shahin et al 2012;Zerilli et al 2018). Other papers (Lien & Mannseth 2008;Wirianto et al 2010) show how one can deal with typical challenges of 4-D CSEM analysis such as noise, measurement and modelling errors, by means of for example optimizing acquisition geometry.…”

Section: Introductionmentioning

confidence: 99%

“…Andreis & MacGregor 2011). Besides, there exist a few other studies that used inversion of CSEM data to determine 4-D responses in the model domain (Ziolkowski et al 2010;Black et al 2011;Liang et al 2012;Colombo & McNeice 2013;Kang et al 2015;Patzer et al 2017). However, none of them investigated the effect of acquisition non-repeatability on the quality of the inverted 4-D response.…”

Section: Introductionmentioning

confidence: 99%

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Time-lapse CSEM: how important is survey repeatability?

Shantsev

Nerland

Gelius

2020

Geophysical Journal International

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Summary An important concern for time-lapse studies using the controlled-source electromagnetic (CSEM) method is repeatability of acquisition parameters for the base and monitoring surveys. We consider a challenging case when variations in source and receiver positions, conductivity of seawater etc. will lead to differences in the recorded EM fields that exceed EM response due to production-induced changes in the reservoir resistivity. We show that even in that case, 4D response can often be clearly resolved if the base and monitor EM datasets are inverted to produce 3D resistivity distributions. More precisely, for a synthetic model of the Snøhvit gas field, changes in the inverted resistivity maps caused by such non-repeatability will be at least 10 times smaller than the time-lapse differences in the reservoir resistivity. By contrast, measurement errors and poor knowledge of background resistivity may reduce the resolution of 4D CSEM to a much stronger degree. Analysis of field CSEM data from the Wisting oil field supports our conclusion about strongly relaxed repeatability requirements when 4D effects are established by examining inverted resistivity volumes rather than by looking at raw EM data.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Time-lapse CSEM: how important is survey repeatability?

Shantsev

Nerland

Gelius

2020

Geophysical Journal International

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“…A similar joint inversion workflow used for joint inversion of controlled-source electromagnetic and production data can be found in Liang et al (2012). A similar joint inversion workflow used for joint inversion of controlled-source electromagnetic and production data can be found in Liang et al (2012).…”

Section: Introductionmentioning

confidence: 99%

Joint inversion of time-lapse crosswell seismic and production data for reservoir monitoring and characterization

2013

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We present a fluid-flow constrained inversion approach for joint interpretation of time-lapse seismic and production data. In this approach, the full-waveform seismic inversion is integrated into the traditional history-matching process. Hence, the interpretation of time-lapse seismic data is constrained by the fluid-flow physics in the reservoir. The key component in the workflow is a fluid-flow simulator, which computes not only the production data in the wells, but also the temporal and spatial distribution of fluid properties, such as fluid saturation and pressure. These fluid properties, together with prior rock properties, can be transformed to acoustic properties using the prescribed petro-elastic model. A finite-difference frequency-domain acoustic solver is then used to simulate the time-lapse seismic responses on the reservoir. We use a multiplicative-regularized Gauss-Newton scheme to update the reservoir model iteratively until good match between measured and simulated data is achieved. The derivative of seismic data with respect to acoustic properties is calculated using the adjoint method, and then connected to reservoir parameters using a chain rule derived from the petro-elastic model, while the derivative of production data with respect to reservoir parameters is calculated using the gradientsimulator method. A synthetic crosswell example is employed to demonstrate that the estimation of permeability and flooding front movement can be significantly improved from the joint inversion of time-lapse seismic and production data.

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Seafloor bathymetry in deep and shallow water marine CSEM responses of Nigerian Niger Delta oil field: Effects and corrections

Folorunso

2015

Journal of Applied Geophysics

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Joint inversion of controlled-source electromagnetic and production data for reservoir monitoring

Cited by 7 publications

References 36 publications

Time-lapse CSEM: how important is survey repeatability?

Time-lapse CSEM: how important is survey repeatability?

Joint inversion of time-lapse crosswell seismic and production data for reservoir monitoring and characterization

Seafloor bathymetry in deep and shallow water marine CSEM responses of Nigerian Niger Delta oil field: Effects and corrections

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