Local probabilistic inversion of seismic AVO data

Hansen, H.J.; Jakobsen, Ask

doi:10.3997/2214-4609.201801888

Cited by 3 publications

(4 citation statements)

References 4 publications

(5 reference statements)

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“…This section provides a description of the direct probabilistic inversion (DPI) tool, as described in Hansen and Jakobsen [10] and Mutual et al [11]. The DPI is a single-step inversion process that inverts pre-stack seismic data directly for facies or litho-fluid classes through integration of seismic AVO data, well logs and geological information of spatial facies distribution.…”

Section: Method: Direct Probabilistic Inversionmentioning

confidence: 99%

“…Adding prior information from different domains directly into the inversion can potentially resolve beyond the seismic bandwidth. See Hansen and Jakobsen [10] for more conceptual DPI details. A schematic workflow of the DPI inversion is shown in Figure 3, where the inputs are given as the prior framework (stratigraphical/geological information and well data) and seismic AVO data, whereas the main output is the marginal (pointwise) posterior probability.…”

Section: Method: Direct Probabilistic Inversionmentioning

confidence: 99%

“…Two different seismic inversion approaches were performed: (1) deterministic AVO inversion (the traditional approach) [19,20] and (2) the improved direct probabilistic inversion (DPI) approach [10,17,21]. The basic workflows for the inversions are outlined in Table 2.…”

Section: Inversion Setupmentioning

confidence: 99%

See 2 more Smart Citations

Characterizing a Wedged Chalk Prospect in the Danish Central Graben Using Direct Probabilistic Inversion

Bredesen

Herbert²,

Smit

et al. 2022

Geosciences

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A novel direct probabilistic inversion using seismic pre-stack data as input to characterize a wedged chalk reservoir prospect was demonstrated from the Upper Cretaceous unit, Danish North Sea. The objective was to better resolve the lateral extent and pinch-out of the chalk prospect in a frontier exploration setting and compare the results with a more traditional deterministic inversion and geostatistical reservoir modeling. The direct probabilistic inversion results provided additional reservoir insights that were challenging to obtain from the more traditional workflows and are also more flexible for associated uncertainty assessments. Hence, this study demonstrates the usefulness of such direct probabilistic inversions even with suboptimal data availability.

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Section: Method: Direct Probabilistic Inversionmentioning

confidence: 99%

Section: Method: Direct Probabilistic Inversionmentioning

confidence: 99%

See 1 more Smart Citation

Characterizing a Wedged Chalk Prospect in the Danish Central Graben Using Direct Probabilistic Inversion

Bredesen

Herbert²,

Smit

et al. 2022

Geosciences

View full text Add to dashboard Cite

show abstract

“…Another example of a localized inverse problem is that of inversion of reflection seismic amplitude versus offset data as discussed and utilized by Jullum & Kolbjørnsen (2016) and Hansen & Jakobsen (2018). In seismic inversion using the convolution method, data at one location in depth is sensitive only to the elastic parameters in the vicinity of the data location, as defined by the prior model, noise model, and the wavelet used for convolution.…”

Section: Applications For Localized Inverse Problemsmentioning

confidence: 99%

Efficient probabilistic inversion using the rejection sampler—exemplified on airborne EM data

Hansen

2020

Geophysical Journal International

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Summary Probabilistic inversion methods, typically based on Markov chain Monte Carlo, exist that allow exploring the full uncertainty of geophysical inverse problems. The use of such methods is though limited by significant computational demands, and non-trivial analysis of the obtained set of dependent models. Here, a novel approach, for sampling the posterior distribution is suggested based on using pre-calculated lookup tables with the extended rejection sampler. The method is 1) fast, 2) generates independent realizations of the posterior, and 3) does not get stuck in local minima. It can be applied to any inverse problem (and sample an approximate posterior distribution) but is most promising applied to problems with informed prior information and/or localized inverse problems. The method is tested on the inversion of airborne electromagnetic data and shows an increase in the computational efficiency of many orders of magnitude as compared to using the extended Metropolis algorithm.

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Direct probabilistic inversion for facies with different elastic depth trends

Jakobsen¹

2022

Second International Meeting for Applied Geoscience &Amp; Energy

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Local probabilistic inversion of seismic AVO data

Cited by 3 publications

References 4 publications

Characterizing a Wedged Chalk Prospect in the Danish Central Graben Using Direct Probabilistic Inversion

Characterizing a Wedged Chalk Prospect in the Danish Central Graben Using Direct Probabilistic Inversion

Efficient probabilistic inversion using the rejection sampler—exemplified on airborne EM data

Direct probabilistic inversion for facies with different elastic depth trends

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