Background resistivity model from seismic velocities

Werthmüller, Dieter; Ziolkowski, Anton; Wright, David

doi:10.1190/segam2012-0696.1

Cited by 4 publications

(9 citation statements)

References 15 publications

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“…Many existing electrical-elastic relationships are at least partly empirical (Carcione et al, 2007). In addition to this, the majority of workflows which relate a rock's elastic and electrical properties require the estimation of porosity as an intermediate step (e.g., Carcione et al (2007); Engelmark (2010); Werthmüller et al (2013)), which can be uncertain away from well control. Carcione et al (2007) presented a set of electrical-elastic cross-property models with no explicit porosity terms by substituting pre-existing resistivity-porosity models into pre-existing velocity-porosity models.…”

Section: Introductionmentioning

confidence: 99%

Linking elastic and electrical properties of rocks using cross-property DEM

Cilli¹,

Chapman²

2020

Preprint

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Section: Introductionmentioning

confidence: 99%

Linking elastic and electrical properties of rocks using cross-property DEM

Cilli¹,

Chapman²

2020

Preprint

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“…The results show that the methodology works. By methodology, we mean the estimation of background resistivities from seismic velocities using rock physics, structural constraints, and depth trends, well logs to calibrate the transform, and Bayes to estimate the uncertainty from data, rockphysics parameters and rock-physics models (Werthmüller et al, 2013). Furthermore, it includes short-offset 1D inversions to estimate the anisotropy and improve the shallow part of the resistivity model outside well control, and finally calculate the CSEM responses from this background resistivity model.…”

Section: Discussionmentioning

confidence: 99%

“…The transform was then applied to the seismic velocities to obtain a resistivity model in the form of PDFs. Figure 5 shows the final result of Werthmüller et al (2013). The initial seismic velocities are shown in Figure 5b, together with the measured well log velocities of well 9/23b-7.…”

Section: Velocity-to-resistivity Transformmentioning

confidence: 96%

“…In the approach presented here, we build upon the background resistivity model derived from seismic velocities described in our earlier paper Werthmüller et al (2013). The result is a detailed resistivity model of the subsurface, which suffers from two weaknesses.…”

Section: Introductionmentioning

confidence: 99%

“…Result ofWerthmüller et al (2013): The mode of the background resistivity model is shown in (a), derived from the velocity model in (b); (c) and (d) are the mode with −σ and þσ, respectively; well 9/23b-7 and some major formations are annotated. These resistivities represent horizontal resistivities because they are calibrated with a vertical well log, which mainly measures horizontal resistivities.Interpretation / August 2014 SH119…”

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confidence: 99%

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Predicting controlled-source electromagnetic responses from seismic velocities

2014

Self Cite

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We created a workflow to predict controlled-source electromagnetic (CSEM) responses from seismic velocities and compared the predicted responses with CSEM data. The first step was to calculate a resistivity model from seismic velocities in a Bayesian framework to account for the uncertainties. The second step was to estimate the electric anisotropy and improve the resistivity model for the depths at which there was no well control. The last step was to use this updated resistivity model to forward-model CSEM responses and compare the result with CSEM data. The comparison with real data revealed that the measured CSEM responses were generally within plus and minus one standard deviation of the predicted responses. This workflow was able to predict CSEM responses, which can prove very useful for feasibility studies before acquisition and interpretation after acquisition of CSEM data.

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Applicability of cross‐property differential effective medium model to the joint elastic–electrical properties of reservoir sandstones

Han

Yan

et al. 2022

Geophysical Prospecting

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Joint seismic and controlled-source electromagnetic surveys can reduce uncertainty and improve hydrocarbon quantification. However, the successful interpretation of joint seismic and controlled-source electromagnetic survey data requires a valid rock physics model to link the elastic and electrical rock properties. A cross-property differential effective medium is recently proposed with pores embedded in the mineral matrix. We have presented a technique to test the applicability of the cross-property differential effective medium model to the joint elastic-electrical properties of reservoir sandstones. The method is based on the common employment of measured sample porosity and inverted equivalent pore aspect ratio from cementation exponent for the modelling. Application of the modelling approach to a laboratory joint elasticelectrical dataset shows that there is a systematic discrepancy in the modelled and measured joint elastic-electrical properties. It is also found that an equivalent pore aspect ratio is existing to reasonably predict the trend of the joint elastic-electrical data; however, the porosity used in the modelling is far from their measured values. Conversely, if the measured sample porosity is employed, the mentioned equivalent pore aspect ratio fails to fit either of the measured elastic and electrical rock properties. The results indicate the incapability of the cross-property differential effective medium model for the joint elastic-electrical modelling of reservoir rocks and suggest the requirement of a new model to link the elastic and electrical properties.

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Background resistivity model from seismic velocities

Cited by 4 publications

References 15 publications

Linking elastic and electrical properties of rocks using cross-property DEM

Linking elastic and electrical properties of rocks using cross-property DEM

Predicting controlled-source electromagnetic responses from seismic velocities

Applicability of cross‐property differential effective medium model to the joint elastic–electrical properties of reservoir sandstones

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