Study on Structural and Sedimentary Characteristics and Hydrocarbon Accumulation Conditions of Carbonate Rocks in the Southeastern Margin Slope Belt of the Pre-caspian Basin

Some carbonate structural oil and gas reservoirs have been discovered in the Pre-salt Carboniferous carbonate strata in the southeastern margin of the Pre-Caspian Basin. However, few efforts have been put on accumulation conditions and enrichment scale of carbonate structural-lithologic reservoirs in the southeast margin slope, which impacts and restricts subsequent reserve replacement and exploration benefits. In this paper, the enrichment conditions of large-scale structural-lithologic oil and gas reservoirs in the slope belt were discussed systematically by studying characteristics of structural zone divisions, sequence stratigraphic framework, sedimentary facies, thin reservoir prediction, hydrocarbon migration and accumulation characteristics. The future exploration direction and several key exploration targets of study area were determined. The results obtained in this study conclude that the structures, fault combination and trap distribution differences in the southeastern margin slope belt are characterized by east-west structural zoning, and the slope belt can be further sub-divided into east gentle slope structural zone and east steep structural zone. The results show that the Carboniferous-Permian strata can be divided into 6 s-order structural sequences from SS1 to SS6 and 16 third-order structural sequences from SQ1 to SQ16, and a sedimentary model of carbonate platform with both east and west margins is firstly established in the main target layer KT-II. Two favorable facies mainly developed in the slope belt, including the open intra-platform beach and the platform edge dune beach body. Both of these two facies are continuous and wide distributed in the NS direction, and they are well overlapped with the low-amplitude structure of the gentle slope. The combined prediction method integrating seismic multi-attribute prediction with logging constraint and artificial intelligence inversion based on convolutional neural network deep learning provides a solution to the problems of thin reservoir prediction and lithologic body characterization. Finally, the structural-lithologic hydrocarbon accumulation model of the slope belt with far-source and long-distance compound transportation and accumulation controlled by local structural superimposed beach physical properties barrier is innovatively constructed. Application of this exploration and evaluation technical method provides an effective guidance for scale exploration and discovery of geological reserves of the AK structural zone in the east gentle slope structural zone in the southeast margin of the basin.