An Integrated Workflow for Reservoir Characterization and Production Prediction: Leveraging Heterogeneity Analysis in the Tight Carbonate Reservoirs in Penglai Gas Field

Abstract

A major obstacle in developing the vast tight carbonate reservoir of the Permian Maokou Formation in Penglai Gas Field is to resolve the discrepancy between gas-in-place estimates and recoverable volumes. There are mainly two challenges. First, there is a limited understanding of how pore geometry, rather than porosity alone, controls gas flow in these heterogeneous reservoirs. Second, uncertainty in water saturation calculations using resistivity and Archie's equation can be significant due to complex mineralogy and low porosity. This study addresses the first challenge by establishing a direct link between pore geometry and well productivity. A novel integrated workflow is introduced, which moves beyond conventional analysis by synergistically combining wireline measurements of nuclear magnetic resonance (NMR), borehole images, spectroscopy, and dipole sonic data. The basis of this methodology is a refined pore geometry classification—distinguishing macropores, mesopores, and micropores—developed from a foundation of core NMR measurement, mercury injection capillary pressure (MICP), and borehole image interpretation, to quantitatively describe the complex pore system. The second challenge in water saturation estimation is resolved by a non-electrical measurement derived from a wireline spectroscopy tool. The formation chlorine concentration measured by the spectroscopy tool is proportional to pore water volume and salinity, which allows for the formation fluid typing without using resistivity data. Finally, an integrated method is utilized for production prediction from an integrated study of mineralogy, porosity, pore geometry, image derived dissolution porosity, permeability, stoneley mobility, water saturation, and other key properties. The standardized classification of litho-facies based on mineralogy, formation structure, and pore geometry provides valuable guidance for the reservoir quality classification, which also serves as critical input for the production prediction model. This classification proves to be very robust in production prediction, as well-connected macropores are shown to contribute significantly to high initial production rates. The chlorine measurement from spectroscopy has a depth of investigation (DOI) of approximately 8-10 inches for 90% of the signal response. The different DOI of various measurements must be accounted for during the fluid typing analysis. Chlorine-based fluid typing serves as a valuable complementary method to resistivity for quantifying water saturation in tight carbonates, particularly where resistivity-based method is challenging in tight carbonate reservoirs. Higher success rates for fluid identification are then achieved. This workflow provides a practical and effective technique for geologists and engineers to accurately target the best pay zones in tight carbonates, thereby optimizing exploration and development strategies. The approach has been validated in the Penglai Gas Field of Sichuan Basin and is directly applicable to similar reservoirs elsewhere.