Gas Reservoir Characterization Using Lp-Norm Constrained High-Resolution Seismic Spectral Attributes
- PDF / 4,826,778 Bytes
- 17 Pages / 547.087 x 737.008 pts Page_size
- 23 Downloads / 240 Views
Pure and Applied Geophysics
Gas Reservoir Characterization Using Lp-Norm Constrained High-Resolution Seismic Spectral Attributes TIEYI WANG,1 SANYI YUAN,1
RUI WANG,2 SHAN YANG,1 and SHANGXU WANG1
Abstract—Reservoir prediction is often a primary objective in seismic exploration, especially for deep hydrocarbon detection with its potential for assessing oil and gas resources. Time–frequency analysis has become a successful method for detecting subsurface features and can also be used to identify potential hydrocarbon reservoirs. However, current applications for hydrocarbon detection often occur at low resolution, due to the influence of the windowing functions and lack of prior constraints, thereby affecting gas prediction for thin reservoirs. To rectify this issue, we investigate the use of sparse inverse spectral decomposition (SISD) based on the wavelet transform, which adopts an lp norm to constrain the time–frequency spectra, and thereby provides a more highly concentrated time–frequency representation than conventional spectral decomposition techniques. The main objective of this paper is to investigate the performance of spectral attributes derived from lp-norm constrained SISD and its application to the characterization of deep-marine dolomite reservoirs in southwest China. The gas-bearing zones in target reservoir are predicted well by extracting and analyzing the spectral amplitude responses of different frequency components. The predicted favorable gasbearing areas are closely related to local structures in the target reservoir, which are also in good agreement with gas-testing results at three well locations and may be used to guide subsequent exploration well development in this region. Keywords: Sparse inverse spectral decomposition (SISD), dolomite reservoirs, gas prediction, lp norm.
1. Introduction Oil and gas reservoir detection is one of the key objectives in seismic exploration, as it is important for predicting, monitoring and optimizing the
1
State Key Laboratory of Petroleum Resources and Prospecting, CNPC Key Laboratory of Geophysical Exploration, China University of Petroleum, Changping, Beijing 102249, China. E-mail: [email protected] 2 Exploration and Production Research Institute, Sinopec, Beijing 100083, China.
performance of an oilfield during production (Sancevero et al. 2006). Seismic inversion has been a commonly used technique in hydrocarbon detection and reservoir characterization (Yuan et al. 2019a), making use of both pre-stack and post-stack seismic data. The most commonly used and effective pre-stack hydrocarbon prediction methods are based on amplitude versus offset (AVO) inversion (Ostrander 1984). Although several improved AVO inversion algorithms have been introduced over the years (e.g., Castagna and Backus 1993; Yin and Zhang 2014), the method still suffers from some limitations. For instance, to obtain an accurate gas reservoir distribution in deep formations, the input data for AVO inversion must be of high signal-tonoise ratio (S/N) and contain amplitude informa
Data Loading...
