中国石化西南油气分公司勘探开发研究院,四川,成都,610041
[ "赵迪(1984—),男,硕士,副研究员,主要从事地震地质综合研究工作。地址:四川省成都市高新区吉泰路688号,邮政编码:610041。E-mail:279665146@qq.com" ]
纸质出版:2023
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赵迪, 马森, 操延辉. 中江气田沙溪庙组地震岩石物理分析与预测模式建立[J]. 油气藏评价与开发, 2023,13(5):608-613.
ZHAO Di, MA Sen, CAO Yanhui. Seismic rock physics analysis and prediction model establishment of Shaximiao Formation in Zhongjiang Gas Field[J]. Petroleum Reservoir Evaluation and Development, 2023, 13(5): 608-613.
赵迪, 马森, 操延辉. 中江气田沙溪庙组地震岩石物理分析与预测模式建立[J]. 油气藏评价与开发, 2023,13(5):608-613. DOI: 10.13809/j.cnki.cn32-1825/te.2023.05.008.
ZHAO Di, MA Sen, CAO Yanhui. Seismic rock physics analysis and prediction model establishment of Shaximiao Formation in Zhongjiang Gas Field[J]. Petroleum Reservoir Evaluation and Development, 2023, 13(5): 608-613. DOI: 10.13809/j.cnki.cn32-1825/te.2023.05.008.
中江气田沙溪庙组气藏勘探开发潜力较大,但以特低孔特低渗储层为主,储层非均质性较强。针对前期岩性和含气性识别可靠性不高、储层孔隙度和厚度预测结果精度较低等问题,开展了较系统的地震岩石物理分析。主要通过正演模拟、流体替换和岩石物理量版等技术手段,进行了储层预测可行性分析,明确了地震弹性参数与气藏岩性参数、储集参数的具体关系,优选了岩性、物性和含气性敏感参数,建立了储层定性预测模式和定量预测模式,即采用最大波谷属性、最小波阻抗属性和最小纵横波速度比预测储层展布。采用纵横波速度比-纵波阻抗交会识别岩性和含气性,并且用纵横波速度比拟合或协模拟定量预测泥质含量,在砂岩内采用纵波阻抗拟合或协模拟定量预测孔隙度,在含气砂岩内采用Lamda/Mu(拉梅系数/剪切模量)拟合或协模拟定量预测含气饱和度,为研究区沙溪庙组储层精细预测夯实了基础。
Shaximiao Formation gas reservoir in Zhongjiang Gas Field has great exploration and development potential. However
it is primarily characterized by ultra-low porosity and ultra-low permeability
with pronounced reservoir heterogeneity. Addressing the challenges related to the early-stage reliability of lithology and gas-bearing identification
as well as the accuracy of reservoir porosity and thickness predictions
a comprehensive seismic rock physics analysis was undertaken. The analysis focused on assessing the feasibility of reservoir prediction through forward modeling
fluid substitution
and rock physics scaling. The objective was to elucidate the specific relationship between seismic elastic parameters
lithological parameters
and reservoir parameters for gas reservoirs. By optimizing sensitive parameters related to lithology
physical properties
and gas-bearing properties
qualitative and quantitative prediction models for reservoirs were established. This entailed using attributes such as the maximum trough attribute
minimum wave impedance attribute
and the ratio of minimum longitudinal and transverse wave velocities to predict reservoir distribution. The lithology and gas-bearing property are identified by P-wave velocity ratio and P-wave impedance intersection. The shale content is quantitatively predicted by P-wave velocity ratio fitting or co-simulation. The porosity is quantitatively predicted by P-wave impedance fitting or co-simulation in sandstone. The gas saturation is quantitatively predicted by Lamda/Mu fitting or co-simulation in gas-bearing sandstone
which lays a solid foundation for the fine prediction of Shaximiao reservoir in the study area.
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