Application of geological modeling constrained by body of volcano rock in Xushen gas field

Abstract

Volcanic reservoir belongs to the event deposits. So it is difficult to distinguish volcanic reservoir and sedimentary pyroclastic rock which is non-reservoir by conventional geological modeling methods. There is less wells in the study area, so the inter-well prediction accuracy is low. In respect of the issues above, the paper puts forward body of volcanic rock as constraint of neural network modeling. Firstly, based on the differences in seismic reflection characteristics between volcanic rocks and surrounding sedimentary pyroclastic rocks, volcano body are identified and characterized in 3D space which is also guided by the volcanic eruption model. Secondly, the most sensitive electrical parameters for volcanic reservoir prediction are optimized based on the reservoir evaluation results. The quantitative relationship between various seismic attributes and reservoir electrical parameters is established by neural network algorithm. Finally, constrained by the volcano body 3D geological model is established by using the neural network algorithm, which objectively reflects the distribution of volcanic mechanism and its internal attributes.A horizontal well in Xushen A block is optimized and designed by this method. The actual drilling reservoir is in good agreement with the prediction. For under-developed volcanic gas reservoirs, the model is established constrained by body of volcano rock to avoid the interference of sedimentary pyroclastic rock in the prediction. Deterministic method of neural network algorithm is applied to obtain the correlation between seismic attributes and reservoir parameters, thus reducing the uncertainty of inter-well prediction. Method of neural network geological modeling constrained by body of volcano rock begins with the reservoir sedimentary characteristics, and fully combines seismic data and drilling data by the neural network algorithm, which reduces the uncertainty of the model to the greatest extent. The paper provides methods and ideas to 3D geology modeling of volcanic rocks reservoir and other similar reservoir.