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基于全道集叠前反演的页岩气优质页岩储层厚度预测 被引量:1

Prediction of Post-Reservoir Thickness of High-Quality Shale Gas Shale Based on Pre-Stack Inversion of Full Stack Gathers
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摘要 四川盆地及周缘广泛发育六套海相、海陆过渡相及陆相页岩地层,五峰组–龙马溪组海相页岩是最有利的勘探开发层系,优质页岩厚度20~80米。目前,四川盆地下志留统龙马溪组海相页岩气工作已经进入大规模效益开发阶段,开钻井上千口,完钻井接近1000口。开展优质页岩精细预测,引导布井位置的优选,提高优质储层的钻遇率,是页岩气勘探——开发一体化的迫切需要。本论文以四川盆地Z地区为例,将基于全道集叠前反演应用于生产实践,预测页岩气水平井目标靶体储层厚度,指导水平井轨迹设计。结果表明:基于全CRP道集叠前反演技术充分利用了原始道集中完整的AVO信息,解决了目前页岩气优质页岩储层识别的难题,帮助划分页岩气的有利区,提高了页岩气水平井钻探成功率,降低了勘探开发成本。 Six sets of marine facies, marine-terrestrial transition facies and continental shale strata are widely developed in the Sichuan Basin and its periphery. The O3w~S1l1 Formation marine shale is the most favorable formation for exploration and development, and its high-quality shale is about 20~80 meters thick. At present, the Lower Silurian Longmaxi Formation marine shale gas in the Sichuan Basin has entered a large-scale profitable development stage. More than 1,000 wells have been drilled and nearly 1,000 have been completed. Carrying out fine predictions of high-quality shale, guiding the deployment of well positions, and increasing the drilling encounter rate of high- quality reservoirs are all urgent needs for the integration of shale gas exploration and development. This thesis takes the Z area of the Sichuan Basin as an example, and applies the pre-stack inversion based on the complete set in production practice to predict the reservoir thickness of the target body of a shale gas horizontal well, thereby guiding the design of the horizontal well trajectory. The results show that the pre-stack inversion technology based on the full CRP gathers makes full use of the complete AVO information of the original gathers, which not only solves the current problem of identifying high-quality shale gas shale reservoirs, but also helps to distinguish favorable areas for shale gas. While increasing the drilling success rate of shale gas horizontal wells, it also reduces exploration and development costs.
出处 《地球科学前沿(汉斯)》 2022年第3期386-395,共10页 Advances in Geosciences
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