基于区域地质图与数字高程模型的地层埋深预测方法及应用

Method for predicting formation buried depth based on regional geological maps and digital elevation model and its application

对于页岩气、水溶气等非常规天然气资源早期选区评价,往往因为缺乏地震资料导致难以依赖地震构造解释获得目的层的埋深,故借助其他非地震资料有效预测目的层区域性埋深具有重要意义。区域地质图与数字高程模型(DEM)都是广泛覆盖且容易获取的基础性资料。利用区域地质图蕴含的地层产状、地下构造起伏趋势、地层埋深和地表出露地层年代的关系等信息,再叠合DEM地表高程,建立了一种有效预测目的层构造高度和埋深的新方法。利用四川盆地及周缘地区36幅1∶20万区域地质图和美国航空航天局(NASA)数字高程模型资料,预测了该区下志留统龙马溪组底界埋深,据此编制的龙马溪组底界埋深等值线图为该区页岩气保存条件评价提供了重要参数。该方法不仅可为页岩气早期选区评价提供有效支撑,还可应用于深部高压含水层中水溶气的资源评价、深部咸含水层CO_(2)地质封存的构造优选。

[Objective]For the early selection and evaluation of unconventional gas resources such as shale gas and dissolved gas,it is often difficult to obtain formation burial depth by seismic structural interpretation due to the lack of seismic data.Therefore,it is necessary to effectively predict the burial depth of the target layer using other non-seismic data.[Methods]Both regional geological maps and digital elevation model(DEM)are widely covered and easily accessible basic data.In this study,a new method for predicting structural height and buried depth of target layer is established by superposing regional DEM information with geological map which contains the attitude of stratum,trend of underground structures,as well as the relation between buried depth of underground layer and age of surface layer.[Results]This method is effective for predicting the burial depth of Marine strata with relatively stable sedimentary thickness.The buried depth of the Lower Silurian Longmaxi Formation in Sichuan Basin and its periphery is predicted based on 36 geological maps with scale of 1∶200000 and DEM data,and then the contour map of the buried depth of Longmaxi Formation provides important parameters for the evaluation of shale gas preservation conditions in this area.[Conclusion]The method of predicting the burial depth of Marine strata by using non-seismic data such as regional geological map and DEM can not only provide effective support for the early selection evaluation of shale gas,but also can be applied to the resource evaluation of water-soluble gas in deep high-pressure aquifers and the structural optimization of CO_(2) geological storage in deep saline aquifers.