NEW WELL RESEARCH TECHNOLOGY IS THE KEY TO THE INTEGRATED DEVELOPMENT OF OIL AND GAS FIELDS
Bibliographic record
Abstract
A detailed analysis of the available nuclear methods for well logging was carried out to select an effective technology from the point of view of obtaining true petrophysical data characterizing the formation matrix and fluid saturation at a specific point of time. The goal of these process is research currently available nuclear technologies designed for the Oil and Gas field formation evaluation and to review results of the implementation of QUAD NeutronTM (product of Roke Technologies Ltd (Canada)) in old wells in Ukraine. Reviewed are pulsed neutron technologies available from leading International Logging Companies, which are widely used in Ukraine, including the QUAD NeutronTM, to determine primary petrophysical properties and the reservoir saturation characteristics. Certain criteria have been established that signifi cantly impacted quality of the data analysis during interpretation. These included the number of casing strings installed, absence of Open Hole data as input, drill bit size, presence or absence of cement in the annulus and several others. The advantages and disadvantages of each of the systems are shown and effective examples of application with recommendations and test results are provided in this paper. Since 2009 QUAD NeutronTM was successfully utilized in more than 3000 wells worldwide. The geography of technology application covers such countries as Canada, USA, Russia, Azerbaijan, Malaysia, Colombia, Venezuela, Peru, China, Nigeria, Mexico, Georgia, Thailand, Kazakhstan, and Saudi Arabia. The following list of IOC, NOC and other international E&P companies contains only some of the users of the data provided by QUAD NeutronTM: Shell, Lukoil, Petronas, Repsol, Cenovus, Talisman, Murphy, Rosne] . «GEO-DELTA-KB» LLC has exclusive rights to QUAD NeutronTM technology on the territory of Ukraine since 2018. Equipment has been used to provide valuable formation evaluation data to such clients as Ukrgasvydobuvannya, Ukrna] a and other domestic companies in the Western and Eastern regions. Data gave been acquired in dozens of old Oil and Gas wells. The obtained results demonstrate the high efficiency of the technology application, especially when making decisions for the reactivation of old wells. Conducted analysis of existing nuclear logging methods allowed selection of the most effective technology as compared under similar conditions. The data obtained as a result of interpretation, together with an understanding of the processes occurring in the wells, contributed to providing reliable information for making informed decisions. The most eff ective application of the QUAD NeutronTM technology in Ukraine appears to be for the reevaluation of old wells with complex design (up to 4 strings of casing) to identify missing pay zones, assess the potential of existing reservoirs, determine the presence or absence of cement in the annulus, waterfl ooding zones, etc. The technology can also be successfully used for evaluating active wells and in openhole wellbores.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".