Petrophysical Analysis of a Thermal Clastic-Siliceous Zone Using Core Data and Borehole Image Log Interpretation to Refine Reservoir Properties for Conglomerate Intervals
Abstract
Conglomerate layers are present in a sand reservoir under thermal recovery, and comprise a significant volume of the zone. The porosity of these conglomerates is lower than that of the interbedded sands and they contain lower volumes of OIP, but how much lower? Image and conventional open-hole logs were used together with core data to characterize the conglomerates, with the goal of deriving an accurate matrix density for improved reservoir porosity calculations Image logs were interpreted to study the sedimentary fabric of conglomerate layers, and numeric grades were assigned to clast size, sorting, packing, roundness, and cementation. Sand and mudstone intervals were also assigned to facies based on image log appearance. Core recovery was poor in conglomerate intervals though good in interbedded sands, and available data were used to identify the rocks comprising the clasts with an estimate of the types most likely to be present in each of the size groups. Rock types are dominantly granodiorites with some Franciscan debris. A material-balance algorithm was used to calculate a matrix density for the conglomerates based on their composition. Matrix densities for sands and siliceous mudstones were calculated from a bulk density transform and their known mineral properties. Porosity was computed from the standard density model and the matrix density curve. Where core data were available, the computed porosity compared well to core. Usually, a shaly sand model would be applied for saturation analysis, but none of the standard clay indicators were useful in this reservoir. Clay volume was low based on core descriptions, so it was determined that the effects of clays could be disregarded and the Archie model was used for saturation. The well was hot due to thermal operations, affecting the measured resistivity, so a transform was developed based on available temperature data to estimate the reservoir temperature from as-logged borehole conditions. Rw was estimated by iterating the Archie model and comparing the results to core saturations. The computed porosity and water saturation show good coherence to core data through the sands, conglomerates, and siliceous lithologies. Water-filled porosity from the dielectric log provided a good cross-check on the saturations from conventional analysis. The results of this study show that integration of rock fabric data from image logs provided an improved estimate of reservoir volume and oil in place.
AAPG Datapages/Search and Discovery Article #90372 © 2020 AAPG Pacific Section Convention, 2020 Vision: Producing the Future, Mandalay Beach, Oxnard, CA, April 4-8, 2020 (Cancelled)