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Record W2789097955 · doi:10.2118/180071-pa

Cryogenic Fracturing of Wellbores Under True Triaxial-Confining Stresses: Experimental Investigation

2018· article· en· W2789097955 on OpenAlexfundno aff
Minsu Cha, Naif B. Alqahtani, Bowen Yao, Xiaolong Yin, Timothy J. Kneafsey, Lei Wang, Yu‐Shu Wu, Jennifer Miskimins

Bibliographic record

VenueSPE Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryNational Energy Technology LaboratoryCMG Reservoir Simulation FoundationU.S. Department of Energy
KeywordsHydraulic fracturingBoreholePermeability (electromagnetism)Overburden pressureOil shaleGeologyPetroleum engineeringGeotechnical engineeringMaterials scienceChemistry

Abstract

fetched live from OpenAlex

Summary A laboratory study of cryogenic fracturing was performed to test its ability to improve oil/gas recovery from low-permeability reservoirs. Our objective is to develop well-stimulation technologies using cryogenic fluids [e.g., liquid nitrogen (LN)] to increase permeability in a large reservoir volume surrounding wells. The new technology has the potential to reduce formation damage caused by current stimulation methods and minimize or eliminate water usage. The concept of cryogenic fracturing is that a sharp thermal gradient (thermal shock) created at the surfaces of formation rocks by applying cryogenic fluid can cause strong local tensile stress and start fractures. We developed a laboratory system for cryogenic fracturing under true-triaxial loading, with LN-delivery/control and -measurement systems. The loading system simulates confining stresses by independently loading each axis up to approximately 5,000 psi on 8×8×8-in. cubes. Temperature in boreholes and at block surfaces and fluid pressure in boreholes were continuously monitored. Acoustic and pressure-decay measurements were obtained before and at various stages of stimulations. Cubic blocks (8 × 8×8-in.) of Niobrara shale, concrete, and sandstones were tested, and stress levels and anisotropies varied. Three schemes were considered: gas fracturing without cryo-stimulation, gas fracturing after low-pressure cryogen flow-through, and gas fracturing after high-pressure cryogen flow-through. Results from pressure-decay tests show that LN stimulation clearly increases permeability, and repeated stimulations further increase the permeability. Acoustic velocities and amplitudes decreased significantly after cryo-stimulation, indicating fracture creation. In the gas fracturing without the stimulation, breakdown (complete fracturing) occurs suddenly without any initial leaking, and major fracture planes form along the plane containing principal-stress and intermediate-stress directions, as expected theoretically. However, in the gas fracturing after cryogenic stimulations, breakdown occurred gradually and with massive leaking because of thermal fractures created during stimulation. In addition, the major fracture direction does not necessarily follow the plane containing the principal-stress direction, especially at low confining-stress levels. In tests, we observed that cryogenic stimulation seems to disrupt the internal stress field. The increase in borehole temperature after stimulation affects the permeability of the specimen. When a stimulated specimen is still cold, it maintains high permeability because fractures remain open and local thermal tension is maintained near the borehole. When the rock warms back, fractures close and permeability decreases. In these tests, we have not used proppants. Overall, fractures are clearly generated by low- and high-pressure thermal shocks. The added pressure of the high-pressure thermal shocks helps to further propagate cryogenic fractures generated by thermal shock. Breakdown pressure is significantly lowered by LN stimulation, with observed breakdown-pressure reductions up to approximately 40%.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations77
Published2018
Admission routes1
Has abstractyes

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