Advanced Porosity Modeling and Lithology Analysis Based on Sonic Log and Core Data for Arkose Sandstone Reservoir: Habban Field

Abstract

Porosity represents the rock’s capacity to trap fluid. It is the main quality indicator for hydrocarbon-bearing reservoirs. The reservoir porosity is a crucial input to estimate hydrocarbon reserves by volumetric method, which is known as oil originally in place (OOIP). It also plays a key role in the hydraulic unit identification, rock typing, net reservoir, and net pay analyses to determine the best potential oil-bearing layers for perforation and oil production. The porosity is also a required input to establish the reservoir static and dynamic models. The quantitative evaluation of porosity is challenging especially during reservoir characterization. Many factors such as mineralogical composition, type and amount of cement, rock texture, grain-packing pattern, and rock compaction would affect its value. A good quantitative evaluation of porosity requires using integrated methods between well logs and core data. The present study is part of an integrated workflow to characterize arkose sandstone reservoir called Kuhlan Formation in the Habban field located in Republic of Yemen. It is one of the most important oil-producing formation in East Yemen region, located in the sedimentary basin called Shabwa–Marib basin. It is deposited in transitional continental environment in the Jurassic Age. The compressional sonic log is initially used in this analysis from five key wells. The sonic porosity by using linear and nonlinear methods is computed over the reservoir depth interval. The sensitivity analysis for fluid slowness, matrix slowness, and compaction factor is conducted. Core samples were taken from two wells and analyzed by using both conventional and special core analyses in the laboratory. Core porosity by using helium method was measured, and the grain density was determined. The X-ray diffraction analyses were conducted on core samples to fully understand the rock lithology and mineralogical bulk composition for this reservoir. Understanding the details of the reservoir lithology and mineralogy is extremely important in the reservoir characterization and production improvement treatments. The comparisons between log porosity and core porosity have been made. The log analysis results show that the linear method is highly sensitive to the changes of matrix slowness and compaction factor. The nonlinear method is insensitive to the changes of fluid slowness and slightly sensitive to the changes of matrix slowness. The analysis also shows that the porosity based on the nonlinear method has a good match with core porosity. The X-ray diffraction analysis shows that the dominant mineral is quartz with average dry weight of 52%; however, this reservoir contains a significant amount of feldspar minerals. The cement is of calcareous nature, and its concentration is more at the upper part of this formation. The clay type is illite, and its volume ranges between 10 and 13%. The average porosity for this reservoir varies between 6 and 11%.