OIL AND GAS POTENTIAL TERRITORIES PREDICTION BASED ON REMOTE SENSING DATA. CASE OF: SKVORTSIVSKO-YULIYIVSK TEST SITE OF THE DNIEPER-DONETS DEPRESSION OF UKRAINE

Author:

Khodorovskyi Artur,Apostolov Alexander,Yelistratova Lesya,Romanciuc Inna

Abstract

The methodological techniques developed were used to estimate the fracture permeability of rocks and predicting hydrocarbon reservoirs on the example of the Skvortsivsko-Yuliyivsk test site of the Dnieper-Donets Depression of Ukraine. The rock fracture permeability was estimated based on the interpretation of the lineaments field structural results by remote sensing data. The boundaries of 8 systems of lineaments and their modal values were selected, and the lineament density maps were compiled. The faults identified on the lineament density maps correspond to faults determined on the basis of geological and geophysical data. Maps of the summarized density of lineaments and their intersection nodes were compiled, which reflect the fracture permeability of rocks. Using spatial probabilistic forecasting techniques, it was found that all the maps of the lineament density field had an impact on the hydrocarbon reservoir placement (from 53% to 67.5% of the objects of study are allocated by separate systems) and were used to assess the territory potential for oil and gas exploration. The use of the complex function of the likelihood ratio made it possible to identify more than 90% of the study objects. Maps of the study area potential forecasting regarding the hydrocarbon reservoirs are compiled using the sliding window with size: 4.5 by 1.5 km and 14 by 4 km, which makes it possible to predict survey objects at different depths. 8 zones were selected based on the analysis of the complex probability function. There are 5 perspective areas selected, which make up 6% of the test site.

Publisher

Faculty of Mining, Geology and Petroleum Engineering

Subject

General Earth and Planetary Sciences,Geology,General Energy,Geotechnical Engineering and Engineering Geology,Water Science and Technology

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