Our understanding of facies and internal connectivity within carbonate platforms is often inadequate despite the fact that carbonate petroleum systems are wide-spread throughout the world, account for ˜50% of world hydrocarbon reserves and have been heavily studied for many years. Petroleum systems modeling routinely used in exploration allows testing different facies distribution / connectivity scenarios and contributes to a better understanding of key uncertainties and reduction of exploration risk. However, if misused or based on insufficient input data, petroleum systems models may generate misleading results and lead to drilling unnecessary dry holes. This is especially true if the resolution of the model is too low or calibration data is sparse.

Regional-scale petroleum systems models of carbonates often miss the critical details such as platform geometry, facies distribution within a platform and high resolution rock flow/seal properties that are required for a proper evaluation of hydrocarbon migration, prediction of pre-drill pressure and estimation of accumulated hydrocarbons. In addition, they typically don’t address syn- and post-depositional factors such as diagenesis and stress history.

For the purpose of this study, a synthetic carbonate platform was built to demonstrate typical problems associated with modeling carbonate petroleum systems and for testing potential hydrocarbon migration and trapping scenarios. It allows simulating petroleum systems which are similar to the Arab and Khuff formations in the Middle East, isolated platforms in Kazakhstan, and others. This presentation will discuss petroleum systems modeling methodology and guide the audience through different low- vs. high-resolution scenarios leading to dramatically different exploration implications.

Petroleum systems modeling (PSM) is an integration of different geological disciplines to analyze the formation and evolution of sedimentary basins and to study processes such as generation, migration, entrapment and preservation of hydrocarbons. PSM estimates mechanical and chemical compaction of sediments and the resulting porosity/permeability, computes pressure, estimates source rock maturity and the degree of kerogen transformation, models multi-component hydrocarbon generation, expulsion and migration, provides likely locations where hydrocarbons are trapped, and estimates composition and volumes of accumulated hydrocarbons. In addition to its primary function, which is to help reduce exploration risk related to hydrocarbon charge, PSM has become very useful in prediction of pre-drill pressure and effective stress, which are utilized in reservoir and seal quality analysis.

Computational complexity of PSM depends on the quality and resolution of seismic and well input data, maturity of the project (exploration, development or production), availability of tectonic/structural/mechanical earth models, and availability of geochemical data. Typical models at present are not too large (several millions grid cells) and the subsurface is represented by relatively simple structured meshes. The utilization of structured meshes often results in inadequately represented internal model boundaries such as faults and may lead to incorrect hydrocarbon migration scenarios.

The availability of high resolution seismic and well data allows for building higher resolution and more complex models, spanning from seismic to nano, hence allowing for more accurate representation of complex features and processes. This requires incorporation of unstructured/adaptive meshes and also the utilization of algorithms that couple poromechanics, basin modeling, seismic data and inversion, and utilization of high performance computing platforms, e.g., GPU- or FPGA-based as well as optimized libraries for solving large, ill-conditioned, sparse matrices.

This talk presents the state-of-the-art in PSM and discusses recommended directions required for addressing future needs of exploration for conventional / unconventional resources and interactions with geomechanics and seismic.