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Integration of rock physics and seismic inversion for rock typing and flow unit analysis: A case study
Author(s) -
Khadem Benyamin,
Saberi Mohammad Reza,
Eslahati Mohammad,
Arbab Bita
Publication year - 2020
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.12952
Subject(s) - geology , seismic inversion , igneous petrology , petrology , permeability (electromagnetism) , workflow , reservoir modeling , engineering geology , hydrogeology , seismic to simulation , lithology , geophysics , petroleum engineering , geotechnical engineering , seismology , geometry , computer science , volcanism , genetics , mathematics , database , azimuth , membrane , biology , tectonics
Rock typing and flow unit detection are more challenging in clastic reservoirs with a uniform pore system. An integrated workflow based on well logs, inverted seismic data and rock physics models is proposed and developed to address such challenges. The proposed workflow supplies a plausible reservoir model for further investigation and adds extra information. Then, this workflow has been implemented in order to define different rock types and flow units in an oilfield in the Persian Gulf, where some of these difficulties have been observed. Here, rock physics models have the leading role in our proposed workflow by providing a diagnostic framework in which we successfully differentiate three rock types with variant characteristics on the given wells. Furthermore, permeability and porosity are calculated using the available rock physics models to define several flow units. Then, we extend our investigation to the entire reservoir by means of simultaneous inversion and rock physics models. The outcomes of the study suggest that in sediments with homogeneous pore size distribution, other reservoir properties such as shale content and cementation (which have distinct effects on the elastic domain) can be used to identify rock types and flow units. These reservoir properties have more physical insights for modelling purposes and can be distinguished on seismic cube using proper rock physics models. The results illustrate that the studied reservoir mainly consists of rock type B, which is unconsolidated sands and has the characteristics of a reservoir for subsequent fluid flow unit analysis. In this regard, rock type B has been divided into six fluid units in which the first detected flow unit is considered as the cleanest unit and has the highest reservoir process speed about 4800 to 5000 mD. Here, reservoir quality decreases from flow unit 1 to flow unit 6.