Download or read book 3D Seismic Attribute Analysis and Machine Learning for Reservoir Characterization in Taranaki Basin, New Zealand written by Aamer Ali AlHakeem and published by . This book was released on 2018 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The Kapuni group within the Taranaki Basin in New Zealand is a potential petroleum reservoir. The objective of the study includes building a sequential approach to identify different geological features and facies sequences within the strata, through visualizing the targeted formations by interpreting and correlating the regional geological data, 3D seismic, and well data by following a sequential workflow. First, seismic interpretation is performed targeting the Kapuni group formations, mainly, the Mangahewa C-sand and Kaimiro D-sand. Synthetic seismograms and well ties are conducted for structural maps, horizon slices, isopach, and velocity maps. Well log and morphological analyses are performed for formation sequence and petrophysics identification. Attribute analyses including RMS, dip, azimuth, and eigenstructure coherence are implemented to identify discontinuities, unconformities, lithology, and bright spots. Algorithmic analyses are conducted using Python programming to generate and overlay the attributes which are displayed in 3D view. Integrating all of the attributes in a single 3D view significantly strengthens the summation of the outputs and enhances seismic interpretation. The attribute measurements are utilized to characterize the subsurface structure and depositional system such as fluvial dominated channels, point bars, and nearshore sandstone. The study follows a consecutive workflow that leads to several attribute maps for identifying potential prospects"--Abstract, page iv.