Information about reservoir properties usually comes from two sources: seismic data and well logs. The former provide an indirect, low resolution image of rock velocity and density. The latter provide direct, high resolution (but laterally sparse) sampling of these and other rock parameters. An important problem in reservoir characterization is how best to combine these data sets, allowing the ...

this paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3d seismic data. to this end, an actual carbonate oil field in the south-western part ofiranwas selected. taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values.  seismic surveying was performed next on these models. f...

Reservoir characterization plays an important role in different parts of an industrial project. The results from a reservoir characterization study give insight into rock and fluid properties which can optimize the choice of drilling locations and reduce risk and uncertainty. Delineating hydrocarbon bearing zones within a reservoir is the main objective of any seismic reservoir characterization...

reservoir characterization plays an important role in different parts of an industrial project. the results from a reservoir characterization study give insight into rock and fluid properties which can optimize the choice of drilling locations and reduce risk and uncertainty. delineating hydrocarbon bearing zones within a reservoir is the main objective of any seismic reservoir characterization...

Shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. However, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. In order to overcome these problems, in this study, a joint inversion strategy is proposed based on the particle swarm optimization (PSO) algorithm. The ...

With the development of computational power, there has been an increased focus on data-fitting related seismic inversion techniques for high fidelity seismic velocity model and image, such as full-waveform inversion and least square migration. However, though more advanced than conventional methods, these data fitting methods can be very expensive in terms of computational cost. Recently, vario...

We determine upper mantle seismic velocity heterogeneities below Southern California from the inversion of teleseismic travel-time residuals. Teleseismic P-wave arrival times are obtained from three temporary passive experiments and Southern California Seismic Network (SCSN) stations, producing good raypath coverage. The inversion is performed using a damped least-squares conjugate gradient met...

Seismic Inversion methods have been routinely used for estimating attributes like P-impedance, Simpedance, density, ratio of P-wave and S-wave velocity and elastic impedances from seismic and well log data. These attributes help to understand lithology and fluid contents in the subsurface. The objective of this research is to use several standard seismic post-stack inversion methods for reservo...

In the seismic inversion model, as the neural network algorithm there are some problems, the convergence bad, accuracy is not high. This paper presents a seismic inversion based on artificial fish Swarm Optimization neural network models. First to initialize fish mapping of chaos optimization and ergodicity of artificial fish-swarm search and adaptive strategies of artificial fish-swarm algorit...

The focus of our study is lithology/fluid inversion with spatial coupling from prestack seismic amplitude variation with offset AVO data and well observations. The inversion is defined in a Bayesian setting where the complete solution is the posterior model. The prior model for the lithology/fluid LF characteristics is defined as a profile Markov randomfield model with lateral continuity. Each ...