Seismic inversion for acoustic impedance and porosity of Cenozoic cool-water carbonates on the upper continental slope of the Great Australian Bight

2005 ◽  
Vol 215 (3-4) ◽  
pp. 123-134 ◽  
Author(s):  
M. Huuse ◽  
D.A. Feary
Keyword(s):  
Continental Slope ◽  
Acoustic Impedance ◽  
Seismic Inversion ◽  
Cool Water ◽  
Great Australian Bight

scholarly journals Petrophysical seismic inversion based on lithofacies classification to enhance reservoir properties estimation: a machine learning approach

2020 ◽  
Author(s):  
Amir Abbas Babasafari ◽  
Shiba Rezaei ◽  
Ahmed Mohamed Ahmed Salim ◽  
Sayed Hesammoddin Kazemeini ◽  
Deva Prasad Ghosh
Keyword(s):  
Acoustic Impedance ◽  
Reservoir Characterization ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Well Location ◽  
The Neural Network ◽  
Machine Learning Approach ◽  
Lithofacies Classification ◽  
Elastic Inversion ◽  
Significant Match

Abstract For estimation of petrophysical properties in industry, we are looking for a methodology which results in more accurate outcome and also can be validated by means of some quality control steps. To achieve that, an application of petrophysical seismic inversion for reservoir properties estimation is proposed. The main objective of this approach is to reduce uncertainty in reservoir characterization by incorporating well log and seismic data in an optimal manner. We use nonlinear optimization algorithms in the inversion workflow to estimate reservoir properties away from the wells. The method is applied at well location by fitting nonlinear experimental relations on the petroelastic cross-plot, e.g., porosity versus acoustic impedance for each lithofacies class separately. Once a significant match between the measured and the predicted reservoir property is attained in the inversion workflow, the petrophysical seismic inversion based on lithofacies classification is applied to the inverted elastic property, i.e., acoustic impedance or Vp/Vs ratio derived from seismic elastic inversion to predict the reservoir properties between the wells. Comparison with the neural network method demonstrated this application of petrophysical seismic inversion to be competitive and reliable.

Improving Porosity–Velocity Relationships Using Carbonate Pore Types

2015 ◽  
Vol 23 (04) ◽  
pp. 1540006 ◽  
Author(s):  
Tingting Zhang ◽  
Yuefeng Sun ◽  
Qifeng Dou ◽  
Hanrong Zhang ◽  
Tonglou Guo ◽  
...  
Keyword(s):  
Pore Structure ◽  
Acoustic Impedance ◽  
Carbonate Rocks ◽  
Seismic Inversion ◽  
Carbonate Reservoir ◽  
Reservoir Rocks ◽  
Fluid Content ◽  
Fracture Fluid ◽  
Poroelastic Model ◽  
Pore Types

Acoustic impedance in carbonates is influenced by factors such as porosity, pore structure/fracture, fluid content, and lithology. Occurrence of moldic and vuggy pores, fractures and other pore structures due to diagenesis in carbonate rocks can greatly complicate the relationships between impedance and porosity. Using a frame flexibility factor ([Formula: see text]) derived from a poroelastic model to characterize pore structure in reservoir rocks, we find that its product with porosity can result in a much better correlation with sonic velocity ([Formula: see text] = [Formula: see text]) and acoustic impedance ([Formula: see text] = [Formula: see text], where A, B, C and D is 6.60, 0.03, 18.3 and 0.09, respectively for the deep low-porosity carbonate reservoir studied in this paper. These new relationships can also be useful in improving seismic inversion of ultra-deep hydrocarbon reservoirs in other similar environments.

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