A fractal model for hydrocarbon resource assessment with an application to the natural gas play of volcanic reservoirs in Songliao Basin, China
Bibliographic record
Abstract
Research Article| September 01, 2012 A fractal model for hydrocarbon resource assessment with an application to the natural gas play of volcanic reservoirs in Songliao Basin, China Caineng Zou; Caineng Zou Research Institute of Petroleum Exploration & Development PetroChina Beijing 100083 China Search for other works by this author on: GSW Google Scholar Qiulin Guo; Qiulin Guo Research Institute of Petroleum Exploration & Development PetroChina Beijing 100083 China Search for other works by this author on: GSW Google Scholar Jinghong Wang; Jinghong Wang Research Institute of Petroleum Exploration & Development PetroChina Beijing 100083 China Search for other works by this author on: GSW Google Scholar Hongbing Xie Hongbing Xie Research Institute of Petroleum Exploration & Development PetroChina Beijing 100083 China Search for other works by this author on: GSW Google Scholar Bulletin of Canadian Petroleum Geology (2012) 60 (3): 166–185. https://doi.org/10.2113/gscpgbull.60.3.166 Article history received: 23 Mar 2011 accepted: 23 Jul 2012 first online: 12 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Search Site Citation Caineng Zou, Qiulin Guo, Jinghong Wang, Hongbing Xie; A fractal model for hydrocarbon resource assessment with an application to the natural gas play of volcanic reservoirs in Songliao Basin, China. Bulletin of Canadian Petroleum Geology 2012;; 60 (3): 166–185. doi: https://doi.org/10.2113/gscpgbull.60.3.166 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter All ContentBy SocietyBulletin of Canadian Petroleum Geology Search Advanced Search Abstract The discovery of large volumes of natural gas from volcanic reservoirs in the Xujiaweizi Sag of Songliao Basin is a milestone in exploration for natural gas reservoired in volcanic rocks in China. Assessing the ultimate gas resource potential of volcanic reservoirs presents a challenge to the operator because the characteristics of volcanic reservoirs differ considerably from conventional clastic reservoirs. There is a need for an appropriate method that provides not only an estimate of remaining resource potential, but also the geographic characteristics of these resources in Xujiaweizi Sag. Statistical analysis on pool size and spatial distributions of 543 oil pools in Nanpu Sag, 911 oil pools in Liaohe Fault Depression, 16 gas pools in Xujiaweizi Sag and the 43 largest oilfields in China suggests that fractal characteristics are common in observed distributions of pool sizes, resource abundance (defined as reserve/unit area), and spatial distribution of oil and gas accumulations. Based on this finding, a two-dimensional fractal stochastic model, using a Fourier transformation power spectrum approach, is proposed to characterize the spatial distribution and estimate the remaining gas resource potential in the volcanic reservoirs. After elimination of high-risk areas and determination of an economic cutoff on resource abundance, this model is used to predict the resource potential under different exploration risk scenarios, as well as possible geographic location of the remaining resources. The application of this model to Xujiaweizi Sag suggests that the remaining gas resource is mostly located in the southeastern part of the sag, providing information on the direction for future exploration of the natural gas in this area. Abstract La découverte de volumes considérables de gaz naturel dans les réservoirs volcaniques de la zone affaissée de Xujia Weizi dans le bassin du Songliao constitue un jalon de l’exploration gazière dans les roches volcaniques en Chine. L’évaluation du potentiel gazier final logé dans les réservoirs volcaniques présente un défi pour l’exploitant, car les caractéristiques des réservoirs volcaniques diffèrent considérablement des réservoirs clastiques conventionnels. Le besoin d’une méthode appropriée existe pour fournir non seulement une estimation des ressources potentielles restantes, mais également les caractéristiques géographiques des ressources en question dans la zone affaissée de Xujia Weizi. Des analyses statistiques sur l’étendue des gisements et la répartition spatiale de 543 gisements pétrolifères dans la zone affaissée de Nanpu, 911 autres dans la zone effondrée et fissurée de Liaohe, 16 gisements gaziers dans la zone affaissée de Xujia Weizi et 43 des plus importants gisements pétrolifères en Chine laissent croire que les caractéristiques fractales sont courantes dans les répartitions observées de l’étendue des gisements, l’abondance des ressources (définies comme réserves/unités de surface) et la répartition spatiale des accumulations pétrolières et gazières. Selon les constatations précédentes, nous proposons un modèle stochastique fractal bidimensionnel en utilisant la méthode de spectométrie par transformation de Fourier, pour caractériser la répartition spatiale et estimer les ressources gazières potentielles restantes dans les réservoirs volcaniques. Après avoir éliminé les secteurs à risques élevés et déterminé la limite économique adéquate sur l’abondance des ressources, le modèle en question permet de prévoir les ressources potentielles, compte tenu de divers scénarios sur les risques de l’exploration, ainsi que la position géographique possible des ressources restantes. L’application de ce modèle dans la zone affaissée de Xujia Weizi suggère que le restant des ressources gazières soit surtout situé dans la partie sud-est de l’affaissement, ce qui nous informe sur l’orientation des futures explorations des sources de gaz naturel dans la région. Michel Ory You do not currently have access to this article.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".