Well Logging Identification Methods for Volcanic Lithofacies in the North of Songliao Basin, China

Abstract

Volcanic lithology and lithofacies are important factors to control the formation of volcanic reservoir. It is a challenge for geologists and petrophysicist to identify lithofacies in the borehole by using well logs. According to the reservoir characters of Daqing volcanic reservoir in Songliao basin, five lithofacies and fifteen su-facies have been recognized through the drilled core analysis of lithology, texture and structure. The relationship between conventional well logs and volcanic lithology can be established by calibrating with core analysis which can be used to identify the rock composition by the established cross-plots. From the FMI measurement, the differences of resistivity values caused by volcanic rock texture and structure can be showed in the image clearly. It shows that four kinds of textures and five kinds of structure can be identified with FMI image. As the volcanic lithofacies marks, specific volcanics lithology, texture and structure corresponds to the specific lithofacies and sub-facies. So lithofacies distribution can be evaluated effectively with the model of volcanics texture and structure combined with rock composition. The results of study indicate that the composition, texture and structure characteristics of the volcanics can be identified by conventional log with FMI measurement, which is important to the further volcanic reservoir exploration and production.

Identification of Shale Lithofacies from FMI Images and ECS Logs Using Machine Learning with GLCM Features

“…Generally, shale lithofacies identification exploits petrophysical measurements, including wireline logs and laboratory core tests [10][11][12]. Due to limited core data in many instances, shale lithofacies are often classified from conventional wireline logs.…”