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Record W2810591888 · doi:10.2118/189972-pa

Generalized Methodology for Estimating Stress-Dependent Properties in a Tight Gas Reservoir and Extension to Drill-Cuttings Data

2018· article· en· W2810591888 on OpenAlexaff
Jaime Piedrahita, Bruno A. Lopez Jimenez, Roberto Aguilera

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersChina National Offshore Oil CorporationPorous Media Laboratory
KeywordsTight gasOverburden pressurePermeability (electromagnetism)Petroleum engineeringCompressibilityEffective stressStress (linguistics)GeologyGeotechnical engineeringDrill cuttingsExponentDrillEngineeringHydraulic fracturingDrillingMechanical engineering

Abstract

fetched live from OpenAlex

Summary The volume of hydrocarbons contained in tight petroleum reservoirs is immense. Thus, their development is crucial to satisfy the worldwide energy demand. A critical aspect for the development of these formations is the stress dependency of rock properties. As pore pressure changes, porosity, permeability, and compressibility of both matrix and natural fractures in tight reservoirs also change, affecting the wells’ production behavior. A practical problem in the estimation of stress-dependent properties is that the amount of core data available to perform the corresponding studies in tight formations is generally scarce. Under these circumstances, drill cuttings can be used to obtain this information. These observations lead to the key objective of this paper: to develop a reliable approach for estimating stress-dependent properties through the introduction of an innovative methodology that quantifies changes in properties of tight reservoirs and how to extend this methodology in drill cuttings. The model developed is based on the relationship between the cube root of normalized permeability and the logarithm of net confining stress defined as confining pressure minus pore pressure applied on the rock. An empirical exponent α is introduced to fit the experimental data from confining tests conducted on both vertical and horizontal core samples. This exponent allows the development of an equation that works independently of the initial net confining stress, which is the main limitation of the models already available in the literature. It is our experience that, in many instances, laboratory tests are run at specific values of net confining stress that do not necessarily match the current stress of the reservoir. The correlation proposed in this paper is valuable because it provides a tool that allows correcting the laboratory results to the appropriate net confining stresses in the reservoir. A statistical analysis is performed to verify the appropriateness of the proposed model for the prediction of rock properties as a function of net confining stress. It is shown that current formulations are particular cases of the proposed model based on the results obtained for the empirical exponent α. Semilog cross-plots of the cube root of normalized permeability versus the net confining stress using core laboratory data corroborate the robustness of the proposed method. The application of the method with drill cuttings is also demonstrated. It is concluded that the proposed method provides a more accurate methodology for estimating stress-sensitive properties of rocks in tight formations, which are usually naturally fractured, such as the Nikanassin formation analyzed in this work. Porosity, permeability, and compressibility of tight formations are estimated by following the generalized methodology proposed in this study.

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How this classification was reachedexpand

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.136
GPT teacher head0.353
Teacher spread0.217 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2018
Admission routes1
Has abstractyes

Explore more

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