中国P站

Abstract

This research synthesizes advanced geophysical data interpretation techniques vital for hydrocarbon exploration and production. It highlights the integration of seismic, well log, and production data with machine learning for improved reservoir characterization. Advances in full-waveform inversion (FWI) and the application of potential field and electromagnetic methods are discussed for enhanced subsurface imaging and delineation. The role of geostatistics in uncertainty quantification and machine learning in automating interpretation is explored. Specific applications of seismic attributes for unconventional reservoirs, time-lapse seismic for reservoir monitoring, and gravity gradiometry for structural analysis are presented. Integration of borehole seismic data further refines reservoir delineation. These methods collectively aim to optimize exploration strategies, reduce risk, and enhance production efficiency.