Petroleum Engineering
Mostafa Zare; Abbdolrahim Javaherian; Mehdi Shabani
Abstract
The aim of seismic inversion is mapping all of the subsurface structures from seismic data. Due to the band-limited nature of the seismic data, it is difficult to find a unique solution for seismic inversion. Deterministic methods of seismic inversion are based on try and error techniques and provide ...
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The aim of seismic inversion is mapping all of the subsurface structures from seismic data. Due to the band-limited nature of the seismic data, it is difficult to find a unique solution for seismic inversion. Deterministic methods of seismic inversion are based on try and error techniques and provide a smooth map of elastic properties, while stochastic methods produce high-resolution maps of elastic properties with the same probability. The current paper studies a stochastic method of seismic inversion which was applied to one of the Persian Gulf oilfields. Joint posterior distribution of elastic properties was calculated using Bayesian principle; then a sequential Gaussian simulation technique was performed to decompose the global probability function of elastic properties into some local probability functions at each trace location. The sampling of the local probability functions was performed, and two hundred realizations of the elastic properties were generated. The results of the stochastic inversion were found to be capable of modeling heterogeneities of the reservoir. The generated realizations provided the possibility to uncertainties assessment by calculating the variance of the elastic properties. It was found out that the uncertainty increased in locations far away from the well. Moreover, stochastic inversion, unlike deterministic one, was found to be capable of detecting thin beds (3.5 to 5.7 m) embedded within the reservoir.
Hamid Reza Ansari; Reza Motafakkerfard; Mohammad Ali Riahi
Abstract
Seismic inversion is a method that extracts acoustic impedance data from the seismic traces. Source wavelets are band-limited, and thus seismic traces do not contain low and high frequency information. Therefore, there is a serious problem when the deterministic seismic inversion is applied to real data ...
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Seismic inversion is a method that extracts acoustic impedance data from the seismic traces. Source wavelets are band-limited, and thus seismic traces do not contain low and high frequency information. Therefore, there is a serious problem when the deterministic seismic inversion is applied to real data and the result of deterministic inversion is smooth. Low frequency component is obtained from well log data; however, but when well log and seismic data are used together, it faces a problem which is a function of the support of scale of measurements. Well log data have a high vertical resolution while seismic data represent low details in vertical direction. Geostatistical seismic inversion (GSI) is a method to overcome the aforementioned limitations. GSI uses well log and seismic data together in the geostatistical frameworks. In this study, a new approach of geostatistical inversion based on spectral geostatistical simulation is used. This approach is performed in frequency domain and stochastic framework. Distinct from sequential simulation, spectral simulation method is a direct method, which does not require an acceptance/rejection step. Hence, GSI algorithm based on spectral simulation is fast. This approach is performed in a case study of an Iranian gas field in the Persian Gulf basin. The upper-Dalan and Kangan are two main formations of this field. The results of GSI are compared with deterministic inversion and it is concluded that, as opposed to deterministic inversion, GSI can recover low frequency components.