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Record W1982690806 · doi:10.2118/2008-072

A Reservoir Economic Indicator to Evaluate a SAGD Project

2008· article· en· W1982690806 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCanadian International Petroleum Conference · 2008
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsHusky Energy (Canada)
Fundersnot available
KeywordsReservoir simulationPetroleum engineeringReservoir modelingComputer scienceReservoir engineeringEnvironmental scienceGeologyPetroleumPaleontology

Abstract

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Abstract The economics of a SAGD project is related to several production performance parameters. The most significant of those are steam-oil ratio (SOR), calendar day oil rate (CDOR), ultimate recovery (recovery factor, RF), and project life. In consequence, these performance parameters are related to reservoir parameters such as reservoir thickness, permeability, oil saturation, porosity, oil viscosity, and other reservoir heterogeneities such as bottom water, top gas, and interbedded shale barriers. It would be useful to find and quantify the correlations between the SAGD performance and reservoir parameters. In this study, a reservoir screening parameter called SPIDER (SAGD Performance Indicator) is developed to evaluate a SAGD project. This new indicator is calculated from four key reservoir parameters such as reservoir thickness (H), permeability (Kv), oil saturation (So), and porosity (Ø) to predict the SAGD performance as well as to evaluate the economics of a SAGD project. A bitumen price and an SOR economic limit are considered to incorporate into a dynamic model. The results show there exists a relationship between SAGD performance parameters (CSOR, CDOR, and RF) and four reservoir parameters with a high correlation coefficient. Especially, there is a linear relationship between SPIDER and NPV with a correlation coefficient of higher than 0.97. This new indicator may be used as a reservoir screening parameter for a SAGD project. Introduction An economic indicator called STEP (Equation 1) was introduced to evaluate the economics of a SAGD project using the production performance parameters such as CSOR, CDOR, and RF in the series of studies (1, 2, 3). Especially, a dynamic model for STEP called STEP-D (Equation 2) was developed to be used as an economic indicator under the changing conditions of the economic limit of SOR and heavy oil price (3). Equation (1) (Available in full paper) Equation (2) (Available in full paper) STEP may be used as an economic criterion on a SAGD project when the SAGD performance parameters are provided from numerical simulation results or field performance data. As reservoir parameters such as reservoir thickness, permeability oil saturation, porosity, and other reservoir heterogeneities impact the SAGD performance, it would be valuable to quantify the impact of these reservoir parameters. There are a few studies regarding the geological parameters impact on thermal process performance. Thimm et al.(4) analyzed the well performance indices with geology for the steam soak phase of the Peace River Expansion Project. Ito and Suzuki (1998) investigated the effect of reservoir parameters on oil production rates in SAGD projects. They found that oil rates are proportional to pay thickness, permeability, movable oil saturation, and porosity. Llaguno et al.(5) proposed a new methodology to determine the potential SAGD application for Venezuela reservoirs. They used an analytical tool to evaluate the impact of the reservoir properties (API gravity, reservoir pressure, thickness, permeability, porosity, oil saturation, oil viscosity) on the SAGD performance. They found that oil rates were mainly affected by pay thickness, porosity, and oil saturation, and SOR was affected by all the properties.

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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 score0.210
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.043
GPT teacher head0.293
Teacher spread0.249 · 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