Joint impedance inversion and spectral decomposition for deepwater gas reservoir characterization: A case study in South China Sea

Author:

Xiang Kun1ORCID,Yang Yadi2,Huang Handong3,Luo Yaneng4ORCID,Jiang Mengqi5ORCID

Affiliation:

1. Formerly Tel Aviv University, Department of Geophysics, Tel Aviv 69978, Israel; presently Sinopec Geophysical Research Institute, Nanjing 211103, China..

2. PetroChina Company Limited, Research Institute of Petroleum Exploration and Development, Beijing 100083, China.(corresponding author).

3. China University of Petroleum Beijing, College of Geophysics, State Key Laboratory of Petroleum Resource and Prospecting, Beijing 102249, China..

4. BGP Inc., China National Petroleum Corporation, Research and Development Center, Zhuozhou 072751, China..

5. PetroChina Huabei Oilfield Company, Research Institute of Exploration and Development, Renqiu 062552, China..

Abstract

Gas reservoir characterization is one of the frontiers in seismic exploration. Acoustic impedance, one of the most effective seismic attributes, aims to describe the spatial distribution of rock properties. However, using acoustic impedance only is insufficient to describe gas-bearing layers accurately, in the case of rapid lithologic changes and complex geology in the deepwater area. The reflection seismograms indicate an absorption effect when seismic waves propagate through gas-bearing layers. The absorption effect can be used as an additional attribute to help gas reservoir characterization. Therefore, we have developed a new attribute for gas reservoir characterization in this study, which integrates the results of acoustic impedance and absorption coefficient. We estimate the acoustic impedance model by using poststack impedance inversion and then we calculate probability distribution functions. Functions are classified into gas-bearing and nongas layers. We discuss an absorption coefficient and obtain it from the spectrum gradient, in which the gradient is calculated by spectral decomposition using the matching pursuit method. We apply the new attribute to characterize the spatial distribution and thickness of deepwater gas reservoirs in the Pearl River Mouth Basin. Well-log and geologic information indicate that the study area has an enrichment of gas reservoirs. Field data application indicates the explicit distribution of the gas reservoir and in accordance with the well-log information, which indicates that our attribute can improve gas reservoir characterization.

Funder

Natural Science Foundation of China

National Science and Technology Major Project

China National Petroleum Corporation

Publisher

Society of Exploration Geophysicists

Subject

Geology,Geophysics

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