ABSTRACT

We performed deterministic reservoir prediction based on inverse rock physics modeling for one oilfield in the West Siberia, Russia. The target zone is Tyumen formation. It consists of a thinly laminated sand-shale-coal sequences. Coal layers have very low acoustic impedance and affect seismic response. The basic idea of the proposed method is to calibrate the rock physics model and then apply it in reverse direction for reservoir properties evaluation. As a result, we transformed seismic scale elastic attributes P-impedance and Vp/Vs ratio into reservoir parameters: volume of clay, volume of coal and porosity.

Presentation Date: Tuesday, September 26, 2017

Start Time: 3:05 PM

Location: 350D

Presentation Type: ORAL

Keywords:
lithology, elastic property, reservoir characterization, seg seg international exposition, artificial intelligence, machine learning, seismic reservoir prediction, coal bed, prediction, rock physics modeling
Subjects:
Reservoir Characterization, Seismic processing and interpretation
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2017. Society of Exploration Geophysicists
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