Coupled Depositional and Diagenetic Numerical Modeling of Evaporite Sedimentary Systems

【摘要】：Evaporites play an important role in various petroleum systems. Extensive evaporite units can provide regional top and/or lateral seals for hydrocarbon reservoirs. They seal over 60% of global hydrocarbons in carbonate reservoirs. Therefore, the distribution and abundance of evaporites represent a key factor in predicting/assessing the carbonate plays and stratigraphic-diagenetic traps. Depositional and diagenetic processes are the two major controls in the formation and development of evaporites. Their quantitative understanding is crucial to enhance reservoir quality and seal integrity prediction. However, the current process-based depositional and diagenetic modeling approaches are different(diffusion vs. reaction-transport), which significantly limits the understanding of the two interacting processes. To overcome this limitation we have developed a novel approach to couple the depositional and chemical processes of evaporite formation and diagenesis. It has been developed and tested for a modern evaporite sedimentary system, the Dead Sea(Jordan Rift Valley), based on geological and environmental data by Warren(2006). First, process-based diagenetic modeling reconstructs possible evaporation pathways(ion concentration variations with increasing salinity) and the resulting diagenetic sequence. Results from diagenetic modeling serve as input framework for subsequent process-based depositional modeling, including evaporite types, threshold salinities for production and effective evaporite sedimentation rates. The results from process-based depositional modeling, constrained by the input from diagenetic modeling, predict the spatial-temporal evolution of evaporites and associated carbonate facies. For subsurface systems, such models significantly improve the characterization and spatial prediction of seal availability and continuity, of stacked carbonate reservoir units, and of the effects of evaporite diagenesis. Moreover, this workflow provides high-resolution integrated depositional-diagenetic models for potential reservoirs. Uncertainties in predicting stratigraphic-diagenetic traps are significantly reduced.