scholarly journals The construction of shale rock physics model and brittleness prediction for high-porosity shale gas-bearing reservoir

2020 ◽  
Vol 17 (3) ◽  
pp. 658-670 ◽  
Author(s):  
Xin-Peng Pan ◽  
Guang-Zhi Zhang ◽  
Jiao-Jiao Chen
Keyword(s):  
Shale Gas ◽  
Rock Physics ◽  
High Porosity ◽  
Shale Rock ◽  
Physics Model ◽  
Rock Physics Model ◽  
Gas Bearing

Improved Rock-Physics Model for Shale Gas Reservoirs

2012 ◽  
Author(s):  
Yaping Zhu ◽  
Shiyu Xu ◽  
Michael Payne ◽  
Alex Martinez ◽  
Enru Liu ◽  
...  
Keyword(s):  
Shale Gas ◽  
Rock Physics ◽  
Gas Reservoirs ◽  
Shale Gas Reservoirs ◽  
Physics Model ◽  
Rock Physics Model

Analyzing the anisotropic characteristics of shale brittleness based on shale rock physics model

2017 ◽  
Author(s):  
Keran Qian ◽  
Zhiliang He ◽  
Xiwu Liu ◽  
Yequan Chen ◽  
Xiangyang Li
Keyword(s):  
Rock Physics ◽  
Shale Rock ◽  
Physics Model ◽  
Rock Physics Model

Two-parameter prestack seismic inversion of porosity and pore structure parameter of fractured carbonate reservoirs: Part 1 — Methods

2018 ◽  
Vol 6 (4) ◽  
pp. SM1-SM8 ◽  
Author(s):  
Tingting Zhang ◽  
Yuefeng Sun
Keyword(s):  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Seismic Inversion ◽  
High Porosity ◽  
Structure Parameter ◽  
Pore Structure Parameter ◽  
Fractured Zones ◽  
Physics Model ◽  
Rock Physics Model

Fractured zones in deeply buried carbonate hills are important because they often have better permeability resulting in prolific production than similar low-porosity rocks. Nevertheless, their detection poses great challenge to conventional seismic inversion methods because they are mostly low in acoustic impedance and bulk modulus, hardly distinguishable from high-porosity zones or mudstones. A proxy parameter of pore structure defined in a rock-physics model, the so-called Sun model, has been used for delineating fractured zones in which the pore structure parameter is relatively high, whereas the porosity is low in general. Simultaneous seismic inversion of the pore structure parameter and porosity proves to be difficult and nontrivial in practice. Although the pore structure parameter is well-defined at locations where density, P-, and S-velocity are known from logs, estimation of P- and S-velocity information, especially density information from prestack seismic data is rather challenging. A three-step iterative inversion method, which uses acoustic, gradient, and elastic impedance from angle-stacked seismic data as input to the rock-physics model for calculating porosity and bulk and shear pore structure parameters simultaneously, is proposed and implemented to solve this problem. The methodology is successfully tested with well logs and seismic data from a deeply buried carbonate hill in the Bohai Bay Basin, China.

scholarly journals A shale rock physics model for analysis of brittleness index, mineralogy and porosity in the Barnett Shale

2013 ◽  
Vol 10 (2) ◽  
pp. 025006 ◽  
Author(s):  
Zhiqi Guo ◽  
Xiang-Yang Li ◽  
Cai Liu ◽  
Xuan Feng ◽  
Ye Shen
Keyword(s):  
Rock Physics ◽  
Brittleness Index ◽  
Barnett Shale ◽  
Shale Rock ◽  
Physics Model ◽  
Rock Physics Model

Anisotropy rock physics model for the Longmaxi shale gas reservoir, Sichuan Basin, China

2017 ◽  
Vol 14 (1) ◽  
pp. 21-30 ◽  
Author(s):  
Xi-Wu Liu ◽  
Zhi-Qi Guo ◽  
Cai Liu ◽  
Yu-Wei Liu
Keyword(s):  
Shale Gas ◽  
Sichuan Basin ◽  
Rock Physics ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Longmaxi Shale ◽  
Physics Model ◽  
Rock Physics Model

Multivariate probabilistic rock physics models using Kumaraswamy distributions

Geophysics ◽  
2021 ◽  
pp. 1-43
Author(s):  
Dario Grana
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Random Variables ◽  
Rock Physics ◽  
Petrophysical Properties ◽  
Kumaraswamy Distribution ◽  
Model Predictions ◽  
Physics Model ◽  
Rock Physics Model

Rock physics models are physical equations that map petrophysical properties into geophysical variables, such as elastic properties and density. These equations are generally used in quantitative log and seismic interpretation to estimate the properties of interest from measured well logs and seismic data. Such models are generally calibrated using core samples and well log data and result in accurate predictions of the unknown properties. Because the input data are often affected by measurement errors, the model predictions are often uncertain. Instead of applying rock physics models to deterministic measurements, I propose to apply the models to the probability density function of the measurements. This approach has been previously adopted in literature using Gaussian distributions, but for petrophysical properties of porous rocks, such as volumetric fractions of solid and fluid components, the standard probabilistic formulation based on Gaussian assumptions is not applicable due to the bounded nature of the properties, the multimodality, and the non-symmetric behavior. The proposed approach is based on the Kumaraswamy probability density function for continuous random variables, which allows modeling double bounded non-symmetric distributions and is analytically tractable, unlike the Beta or Dirichtlet distributions. I present a probabilistic rock physics model applied to double bounded continuous random variables distributed according to a Kumaraswamy distribution and derive the analytical solution of the posterior distribution of the rock physics model predictions. The method is illustrated for three rock physics models: Raymer’s equation, Dvorkin’s stiff sand model, and Kuster-Toksoz inclusion model.

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