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Record W1990705626 · doi:10.2118/64794-ms

Numerical Simulation Study of Water Injection Development in an Extra-low-permeability Fractured Reservoir, Xiaoguai Oilfield

2000· article· en· W1990705626 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Oil and Gas Conference and Exhibition in China · 2000
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyLithologyPermeability (electromagnetism)ConglomeratePorosityOil productionPetrologyWater injection (oil production)Sedimentary rockPetroleum engineeringStructural basinGeotechnical engineeringGeochemistryGeomorphology

Abstract

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Abstract The Xiazijie formation oil pool in Xiaoguai oilfield is a low-porosity, extra-low-permeability, fractured conglomerate reservoir. Based on 3-D detailed geological reservoir description and production performance data, the authors investigate the factors influencing the production of the oil pool with CMG's black oil model (IMEX). Variation and sensitivity of such factors as IPR, location of water injection, production rate, well pattern, direction of well array in relation to fracture orientation and recovery method (solution gas drive vs. Water injection) are analyzed. Introduction Xiaoguai oilfield is located at about 35Km to the south of Karamay, Xinjiang, which lies on the northwestern slop belt of Changji sag between Chepaizi uplift and Zhongguai uplift in northwestern margin of Junggar basin. The target zone Xiazijie Formation is a series which trend north to south, sedimentary thickness average 600~700m. The reservoir lithology is dominated by medium-conglomerate then by arenaceous seriate fine conglomerate, pabbly sandstone and cobblestone. The pore types are mainly composed of micro-fracture, boundary pore, inter-granular dissolved pore and inter-crystalline pore of inter-granular laumontite. Average porosity and permeability are 5.57% and 0.16×10-3µm2, respectively. Reservoir has developed by natural fractures and dominated by the high-angle, right angle of structural genesis, the fracture strike is near EW direction. The fracture porosity and permeability are 0.058% and 36.72×10-3µm2, respectively. This reservoir is a typical low-pore, extra-low-permeability fractured pool and oil saturated with reservoir middle part temperature of 85.5°C, original formation press are of 39.72 MPa, formation press are coefficient of 1.13 and no active edge-bottom water. Since 1996, 154 development wells have been drilled and cumulative oil production is 48.5×10 4t. The main problem during the development is the formation pressure falling fast and the well production declining fast by natural solution gas drive process. Therefore, for this kind of low-pore, extreme-low-permeability fractured reservoir, using what kind of secondary oil recovery process to supplement formation energy is a new subject for oilfield recovery. Model Development and Parameter Preparation Based on the depositional facies belt, reservoir and productivity distribution, G2080 well group that has perfect well pattern and long production history is selected to simulate. The main purposes of study are evaluating the water-flooding effect and predicting production indexes in different recovery processes. Therefore, we selected the black oil simulation software (IMEX) which is made in CMG company Canada, to simulate the 3D 3phases and multitypes of fracture systems. Geologic model development. This model consists of two parts: fracture and matrix, its heterogeneity reflects two aspects: one is heterogeneity between the systems of fracture and matrix, the other is one fracture system. For these reasons, Geotools Software is used to develop the combinative model which is composed of fractures and rocks, and it has basically reflected the heterogeneity distribution of fracture and rocks on 3D space. Grid division. Grid division should be considered to the following several aspects:Simulation modelcontend is needed,Well site should be as on center of grid as possible,The accuracy of calculation result,The direction of reservoir major fractures and plane grid is the same as X, andCalculation speed. Geologic model development. This model consists of two parts: fracture and matrix, its heterogeneity reflects two aspects: one is heterogeneity between the systems of fracture and matrix, the other is one fracture system. For these reasons, Geotools Software is used to develop the combinative model which is composed of fractures and rocks, and it has basically reflected the heterogeneity distribution of fracture and rocks on 3D space. Grid division. Grid division should be considered to the following several aspects:Simulation modelcontend is needed,Well site should be as on center of grid as possible,The accuracy of calculation result,The direction of reservoir major fractures and plane grid is the same as X, andCalculation speed. Grid division. Grid division should be considered to the following several aspects:Simulation modelcontend is needed,Well site should be as on center of grid as possible,The accuracy of calculation result,The direction of reservoir major fractures and plane grid is the same as X, andCalculation speed.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.260
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it