Abstract：Dongdaohaizi Depression is a hydrocarbon-rich depression with abundant oil and gas resources in the Junggar Basin. Due to the low signal-to-noise ratio of seismic data,insufficient resolution and multiples development,processing results have problems of unclear stratigraphic contact,difficult identification of small faults,and difficult prediction of high-quality reservoirs,which seriously restricts the oil and gas exploration in this area. Therefore,this paper employs integrated processing and interpretation technology to increase the signal-to-noise ratio by the GeoEast pre-stack denoising and frequency division in multi-domain and the multiples suppression technology integrating logging and seismic data. Layer-constrained low-frequency weak signal recovery technology and variable step-length predictive deconvolution technology are adopted to effectively broaden the frequency band and improve the resolution of the target layer data. The fault description is significantly improved via velocity field building and migration imaging under well constraints. At the same time,the pre-stack inversion technology of model parameters with shear wave prediction,thereby significantly improving the prediction accuracy of high-quality reservoirs in the target layer. The integrated technology provides a reliable data guarantee for the geological research of the Dongdaohaizi Depression and supports the deployment of several wells in the Dinan area. The drilled Dinan 14 and Dinan 15 wells both achieve a high industrial oil flow of 100 tons per day.
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