Role of bedding planes played in enhancing dissolution in sandstones

Diagenesis exerts an important control on porosity evolution, and research of diagenesis and diagenetic minerals provides insights into reservoir quality evaluation and CO2 storage. Thin section, XRD (X-ray diffraction), CT (Computed Tomography), scanning electron microscopy (SEM), and NMR (Nuclear Magnetic Resonance) tests were used to investigate composition, texture, pore spaces, and diagenesis of sandstones in Paleogene Dongying Formation in Bohai Bay Basin, China, with special aims to unravel diagentic dissolution along bedding planes. The oversized pores, remnants in feldspar-hosted pores, and kaolinite within feldspar grains indicate a high degree of dissolution the framework grains experienced during burial. The CO2-rich or organic acids are responsible for the feldspar dissolution. Grain size plays the primary role in enhancing bedding dissolution process, and bedding planes in fine-medium grained sandstones with high content of feldspars are frequently enlarged by dissolution. The CT scanning image confirms dissolution pores are distributed discontinuously along the bedding planes. The dissolution pores along bedding planes have large pore size, and correspond to the right peak of the bi-modal T-2 (transverse relaxation time) spectrum. The laminated sandstones and siltstones, or sandstones with cross beddings help improve framework grain dissolution. These new findings help improve the understanding of diagenetic models, and have implications in reservoir quality prediction and resource assessments in sandstones.

Automated summary

Diagenesis plays a significant role in controlling reservoir quality. This study investigated the diagenesis of Paleogene sandstones in the Bohai Bay Basin, China using various testing methods. The results reveal the diagenetic dissolution along bedding planes, with feldspar grains experiencing a high degree of dissolution. Grain size and bedding structure are important factors influencing the dissolution process. These findings contribute to a better understanding of diagenetic models and have implications for reservoir quality prediction and resource assessments.