Field development with three‐dimensional seismic methods in the Gulf of Thailand—A case history

Abstract

A three‐dimensional (3-D) marine seismic survey was conducted in the Gulf of Thailand to aid in the development of a gas field indicated by three wildcat wells which had been located by seismic reconnaissance programs shot over a period of several years. The key to successful exploration in the area, basically a hinge line play, was a detailed understanding of the complex faulting controlling the hydrocarbon traps. Since the prospect lies 160–220 km offshore, some specialized surveying techniques were employed to achieve the required positioning accuracy. About 1280 km of seismic data were recorded at 100-m line spacing over a roughly rectangular block covering about [Formula: see text]. The 48‐fold data were processed using a 3-D wave equation migration algorithm yielding a set of seismic traces representing the data vertically below a grid of depth points spaced at [Formula: see text] by 100 m. The results of the 3-D program showed greater fault resolution and structural delineation. The interpretation developed from a series of horizontal slices provided by the 3-D processing further improved fault resolution. Five wells, drilled on the basis of the 3-D survey, are productive and closely tie the seismic data. Initial studies of amplitude patterns of key reflectors, combined with interval velocities from seismic derived logs, appear to offer the potential of direct detection of productive gas zones thicker than 25 to 30 ft. The 3-D seismic data are being utilized for planning additional development wells and potential platform locations.

Modeling GPR data to interpret porosity and DNAPL saturations for calibration of a 3-D multiphase flow simulation

“…Processing and migration is not trivial and must include all geological information from well control and other sources. Oil industry case histories, however, indicate that migration results can be accurate enough to extract detailed geology from the data (Hardage and others 1994;Connelly and others 1991;Morse and others 1987;Dahm and Graebner 1982). The information produced by processing and migration could include values of porosity and DNAPL saturation on a grid with the density of the GPR data, and not the relatively sparse density of the significant interactive forward modeling effort presented here.…”