Abstract
Ukraine ranks the third largest gas reserves in Europe. Gas production is carried out mainly from the Dnieper-Donets Basin (DDB). A gradual decline in reserves is forcing Ukraine to actively search for possible sources to increase reserves by finding bypassed gas intervals in existing wells or exploration of new prospects. This paper describes 3 case studies, where advanced pulsed neutron logging technology has shown exceptional value in gas-bearing layer identification in different scenarios.
The logging technology was applied for formation evaluation. The technology is based on the neutron interaction with the minerals and the fluids contained in the pore space. The logging tool combines measurements from multiple detectors and spacing for self-compensated neutron cross-capture section (sigma) and hydrogen index (HI), and the Fast Neutron Cross Section (FNXS) high-energy neutron elastic cross section rock property. Comprehensive capture and inelastic elemental spectroscopy are simultaneously recorded and processed to describe the elemental composition and the matrix properties, reducing the uncertainties related to drilling cuttings analysis, and overall, the petrophysical evaluation combined with other log outputs.
The proposed methodology was tested in several wells, both in open hole and behind casing. In the study we present its application in three wells from different fields of the DDB. The log data acquisition and analysis were performed across several sandstone beds and carbonates formation with low porosities (<10%), in various combinations of casing and holes sizes. The results showed the robustness and effectiveness of using the advanced pulsed neutron logging (PNL) technologies in multiple cases:
Case Study A: Enabling a standalone cased hole evaluation and highlighting new potential reservoir zones otherwise overlooked due to absence of open hole logs. Case Study B: Finding by-passed hydrocarbon intervals that were missed from log analysis based on conventional open hole logs for current field operator. Case Study C: Identifying gas saturated reservoirs and providing solid lithology identification that previously was questioned from drilling cuttings in an unconventional reservoir.
Evaluation of machine learning methods for formation lithology identification: A comparison of tuning processes and model performances
