Seismic Reservoir Characterisation using Seismic Inversion: A Case Study Showing Importance of Prior Model

Seismic reservoir description using hybrid seismic inversion: A 3D case study from the María Inés Oeste Field, Argentina

The Leading Edge ◽

10.1190/1.1518437 ◽

2002 ◽

Vol 21 (10) ◽

pp. 1002-1008 ◽

Cited By ~ 7

Author(s):

Marcelo Benabentos ◽

Subhashis Mallick ◽

Mario Sigismondi ◽

Juan Soldo

Keyword(s):

Seismic Inversion ◽

Seismic Reservoir ◽

Reservoir Description

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Seismic reservoir characterization of Bone Spring and Wolfcamp Formations in the Delaware Basin — A case study: Part 1

Interpretation ◽

10.1190/int-2019-0294.1 ◽

2020 ◽

Vol 8 (4) ◽

pp. T927-T940

Author(s):

Satinder Chopra ◽

Ritesh Kumar Sharma ◽

James Keay

Keyword(s):

Reservoir Characterization ◽

Rock Physics ◽

Seismic Inversion ◽

Delaware Basin ◽

Seismic Reservoir ◽

Data Conditioning ◽

Inversion Analysis ◽

Sweet Spots

The Delaware and Midland Basins are multistacked plays with production being drawn from different zones. Of the various prospective zones in the Delaware Basin, the Bone Spring and Wolfcamp Formations are the most productive and thus are the most drilled zones. To understand the reservoirs of interest and identify the hydrocarbon sweet spots, a 3D seismic inversion project was undertaken in the northern part of the Delaware Basin in 2018. We have examined the reservoir characterization exercise for this dataset in two parts. In addition to a brief description of the geology, we evaluate the challenges faced in performing seismic inversion for characterizing multistacked plays. The key elements that lend confidence in seismic inversion and the quantitative predictions made therefrom are well-to-seismic ties, proper data conditioning, robust initial models, and adequate parameterization of inversion analysis. We examine the limitations of a conventional approach associated with these individual steps and determine how to overcome them. Later work will first elaborate on the uncertainties associated with input parameters required for executing rock-physics analysis and then evaluate the proposed robust statistical approach for defining the different lithofacies.

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