Geostatistical reservoir characterization constrained by 3D seismic data

Abstract

Geostatistical inversion is developed for constraining a 3D geostatistical realization of acoustic impedance using a 3D seismic block. The geostatistical realization is constructed using a sequential variogram-based approach in such a way that the convolutional response of the realization fits with the actual 3D seismic data. The method is illustrated with a 3D synthetic example. The initial acoustic impedance model is generated using an unconditional simulation of one million grid cells. Then, using five wells 'drilled' in this model and the synthetic seismic obtained by convolution, the geostatistical inversion method is applied to reconstruct the initial acoustic impedance model. The 3D synthetic seismic block is matched in a matter of half-an-hour CPU on a standard workstation. Analysis of the results shows that the input geostatistical model (variograms, means and standard deviations) controls the higher and lower frequencies that are not present in the seismic amplitudes. The use of a '3D earth modelling' tool allows efficient management of the '3D earth model' constructed by geostatistical inversion, and visualization of the various inputs and outputs.

Multidisciplinary stochastic impedance inversion: integrating geological understanding and capturing reservoir uncertainty

“…During the last decade, stochastic impedance inversion methods have been developed and successfully applied on full-field 3D post-stack and AVO seismic data. The development of Elf's (now Total's) geostatistical inversion technique is well documented (Haas & Dubrule 1994;Dubrule et al 1998;Rowbotham et al 1998;Lamy et al 1999;Rowbotham et al 2000). The application of other stochastic methods is described by, for example, Torres-Verdin et al (1999) and Helgesen et al (2000).…”

Reservoir characteristics analysis and favorable area prediction of Zhuhai Formation, Wenchang A oilfield, South China Sea

“…The stochastic inversion technique is adopted in this reservoir inversion, which is based on geostatistics and combines the seismic inversion algorithm with the stochastic sequential simulation algorithm (Haas and Dubrule, 1994;Dubrule O, et al, 1998).…”

“…The frequency-varying AVO inversion technology reduced the ambiguity of the prediction results and improved the prediction accuracy. Geostatistical inversion technique was proposed by Bortoli in 1992 and later improved by Hass, Dubrule et al Geostatistical inversion, which integrates model-based inversion with Markov chain and Monte Carlo simulation algorithms, is a crucial tool for addressing reservoir complexity and heterogeneity (Hass and Dubrule, 1994;Dubrule et al, 1998;Qian et al, 2013).…”

Distribution of gas hydrates on continental margins by means of a mathematical envelope: A method applied to the interpretation of 3D Seismic Data

“…The MFZ and ITZ have been recognized as regions of distributed deformation, generated during the Quaternary, in which BSR distribution clearly depends on local variations in heat flow, tectonic uplift, and sedimentation rates [ Ashi et al ., ; Kinoshita et al ., ]. We demonstrate that BSRs offshore Nankai are distributed within a BSR stability envelope that is quantifiable on 3D seismic data [e.g., Dubrule et al ., ]. The ratio ( R ) between shallow and deep BSRs within the stability envelope is proposed in this work as a method to identify local variations in temperature, pressure, lithology, pore pressure, salinity, tectonic uplift, and subsidence.…”