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We evaluated an advanced forward-modeling-based reservoir characterization technique that uses full elastic finite-difference simulation to investigate the limits of karst identification in stacked seismic data. Identification of karsts is important for field development in carbonated reservoirs because paleokarst features can result in a loss of circulation and/or sometimes lost drill bits. Our primary objective was to verify whether we can detect and interpret the location and size of karsts from seismic data, especially given a complex overburden. We constructed an elastic reservoir model consisting of compressional velocity ([Formula: see text]), shear velocity ([Formula: see text]), and density for the study area using interpreted horizons and well log information. Karsts with varying widths, thicknesses, dip angles, and porosities were inserted to generate multiple versions of the model. We also evaluated the imaging impact of overlying faults and salt on karst detection. Full elastic simulation was performed on the various reservoir models using a realistic acquisition geometry to generate gathers, which were then prestack time migrated to quantify the impact of different karst properties on the seismic images and study the effect of reservoir property changes on the seismic response. Finally, a wave-equation target-oriented analysis was presented to improve the understanding of subsalt amplitude and illumination. From the finite-difference modeling and analysis that we performed, we obtained an uncertainty range on karst property estimation from seismic images and gained insights into future survey design for subsalt interpretation and amplitude analysis. For our specific model, we found the limit of karst identification from seismic data is a 30-m-wide horizontal karst or a 500 m karst dipping at 60°. Also, the karst image width reflected its true width only when the actual karst width was larger than the P-wave wavelength (240 m in this case). With a dipping overburden above the reservoir, apparent positions of karsts were shifted in the updip direction by prestack time migration up to 50 m from their true position. This lateral uncertainty should be kept in mind in well planning to avoid karst features interpreted from a time-migrated seismic section.
We evaluated an advanced forward-modeling-based reservoir characterization technique that uses full elastic finite-difference simulation to investigate the limits of karst identification in stacked seismic data. Identification of karsts is important for field development in carbonated reservoirs because paleokarst features can result in a loss of circulation and/or sometimes lost drill bits. Our primary objective was to verify whether we can detect and interpret the location and size of karsts from seismic data, especially given a complex overburden. We constructed an elastic reservoir model consisting of compressional velocity ([Formula: see text]), shear velocity ([Formula: see text]), and density for the study area using interpreted horizons and well log information. Karsts with varying widths, thicknesses, dip angles, and porosities were inserted to generate multiple versions of the model. We also evaluated the imaging impact of overlying faults and salt on karst detection. Full elastic simulation was performed on the various reservoir models using a realistic acquisition geometry to generate gathers, which were then prestack time migrated to quantify the impact of different karst properties on the seismic images and study the effect of reservoir property changes on the seismic response. Finally, a wave-equation target-oriented analysis was presented to improve the understanding of subsalt amplitude and illumination. From the finite-difference modeling and analysis that we performed, we obtained an uncertainty range on karst property estimation from seismic images and gained insights into future survey design for subsalt interpretation and amplitude analysis. For our specific model, we found the limit of karst identification from seismic data is a 30-m-wide horizontal karst or a 500 m karst dipping at 60°. Also, the karst image width reflected its true width only when the actual karst width was larger than the P-wave wavelength (240 m in this case). With a dipping overburden above the reservoir, apparent positions of karsts were shifted in the updip direction by prestack time migration up to 50 m from their true position. This lateral uncertainty should be kept in mind in well planning to avoid karst features interpreted from a time-migrated seismic section.
Ordovician fractured vuggy carbonate reservoirs, which are deeply buried in the Tazhong Shunnan area in China, are characterized by high heterogeneity. Meanwhile, there is no significant difference between the geophysical characteristics of the reservoirs and that of the surrounding rocks. We have introduced the multiscale stack random medium theory and built some theoretical seismic-geologic models for the fractured vuggy carbonate reservoirs. Furthermore, we obtained the seismic reflection characteristics corresponding to these models using finite-difference forward modeling. The small random vugs are characterized by weak and chaotic reflections with high frequency, and the large vugs are characterized by strong and chaotic reflections with low frequency. The amplitude of the seismic reflections increases with the increasing vug density, and it decreases with the increasing roughness factor. Combining the synthetic reflection characteristics corresponding to the fractured vuggy carbonate reservoirs and the actual seismic reflections from the drilled reservoirs, we summarized the recognition patterns of the carbonate reservoirs. The predicted results found that the potential fractured vuggy reservoirs at the top of Yijianfang Formation are located in the southwest and northeast, in the vicinity of fault zones. The reservoirs in Peng-Laiba Formation are distributed in the northwest of the block.
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