Delineating Plio-Pleistocene channels (gas reservoirs) via seismic attributes in Baltim Gas Field, Nile Delta, Egypt

Abstract

The offshore Nile Delta's Baltim gas fields contain extremely substantial gas condensate accumulations. Therefore, defining Pleistocene reservoirs (El-Wastani formation) and Pliocene reservoirs (Kafr El-Sheikh formation) is the primary objective of this research. A variety of data from five wells, such as gamma-ray, density, neutron, sonic, and resistivity wireline logs. These well logs are put together with seismic data, and a synthetic seismogram is used to find the right gas horizon interpretation for both of anomalies. Using seismic attributes while looking the existing seismic data makes it much easier for interpreters to learn more about the existing geological features. This investigation primarily aims to verify the presence of two potential gas anomalies, first is the structural attributes which include by applying seismic attributes in addition to conventional seismic interpretation. Seismic attributes are significant to ensure the two prospective gas anomalies by applying two different types of seismic attributes. First is the structural attributes which include discontinuity and fault likelihood (FLH), which are very important for fault detection. They are also important for examining the gas leakage to determine if the main fault is fully sealed, partially sealed, or non-sealed. The second is stratigraphic attribute, with different types. In this study, three stratigraphic attributes were applied: sweetness, reflection strength, which is a good tool for gas identification as high sweet points and high reflectivity; also, the third type of attribute is spectral decomposition, which is a good type for channel identification and determine of channel fairway as existence in the second Pliocene anomaly, which reflects the best place for drilling development wells. This study area is illustrated through seismic interpretation of 3D re-processed seismic data collected in 2018 and 5 wells data.