Abstract
This paper presents a pixel-based hierarchical geostatistical modeling of submarine fan turbidite sandstone deposits in Tajin and Agua Fria fields of Chicontepec basin in the Gulf of Mexico. Methods are discussed for identifying and dividing the stack of heterogeneous siliciclastic sediments in these fields, using sequence stratigraphy, petrophysical well log characteristics, geological facies model and 3D seismic data.
An integrated multidisciplinary geostatistical reservoir characterization is conducted in two main steps. First, a large-scale reservoir framework of multiple sequence and subsequence surfaces is constructed based on the integration of data sources of geologic well markers, petrophysics, and seismic horizons. Second, high-resolution 3D distributions of reservoir properties are generated, accounting for inherent inter-relationship among reservoir property data and the three main data scales of log, sub-sequence layer and sequence interval.
At onset, shale volume content in Tajin field and total porosity in Agua Fria field are modeled. Block kriging, trend model, and conditional thickness-weighted Bayesian scheme are presented for the integration of data types and data scales. Facies distributions in Tajin are modeled by indicator kriging conditioned to Vsh content, and hence to seismic. Porosity distributions are by sGsim collocated with Vsh for each facies group, and water saturation distributions are collocated with porosity. Permeability distributions are function of porosity, water saturation, facies and sub-sequences. In Agua Fria, effective porosity and facies are by p-field related methods. Patterns of sand continuity and pay sand connectivity are derived and uncertainty in their prediction is evaluated.
