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Record W2062180051 · doi:10.2118/170851-ms

Injection in Shale: Review of 15 Years Experience on the Norwegian Continental Shelf (NCS) and Implications for the Stimulation of Unconventional Reservoirs

2014· article· en· W2062180051 on OpenAlexaff
F. J. Santarelli, Francesco Sanfilippo, R. W. James, H. H. Nielsen, M. Fidan, Geir Aamodt

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsGeomechanica (Canada)
FundersNorges ForskningsrådConocoPhillips
KeywordsOil shaleGeologyWater injection (oil production)Petroleum engineeringSubseaHydraulic fracturingWellheadSeafloor spreadingInjection wellDispose patternSeismologyGeotechnical engineeringEngineeringGeophysicsPaleontology

Abstract

fetched live from OpenAlex

Abstract Injection in shale with matrix permeability in the nano-Darcy range and without the presence of any permeable layers has been performed for over 15 years on the Norwegian Continental Shelf, for the purpose of cuttings and waste fluids re-injection. The review of this experience shows that, in the early days, many cases of unconfined injection occurred through the vertical propagation of hydraulic fractures over 3000 feet distance that sometimes led to leakages to the seafloor after only a few thousands of barrels had been injected. For avoidance of this, some Operators – e.g. ConocoPhillips Norway – developed techniques allowing wells to dispose of several million barrels into individual shale domains, in safe confined-conditions, with vertical propagation of the disposal domain less than 1000 feet above the injection point. In the case of Ekofisk, this confinement is established by a careful selection of the injection interval and location, a detailed analysis of the injection records and dedicated monitoring programs. Recently, usage of frequent 4D interpretations of seismic surveys shot over a permanent sensor array placed on the seafloor above the field allowed a detailed domain-mapping and independent dynamic-monitoring. The paper focuses on the detailed analysis of those later cases and demonstrates their success from the use of comprehensive field data, which were obtained by the creation of a massively-fractured domain around the injection point – i.e. a conjunction of induced fractures and the opening of pre-existing natural fractures. The analysis of hundreds of pressure fall-off examples shows that the permeability height product (kh) of the shale rock-mass around the injection point reaches several Darcy feet – i.e. orders of magnitude more than during shale reservoir stimulation. One of the cases presented in the paper is used to show how the injection confinement was achieved and how the permeability around the injection zone developed as a function of the injected volume. It shows that after injecting about 10 thousand barrels, the permeability height product (kh) around the injection zone already reached several Darcy feet. The mechanisms responsible for the blockage of the propagation of the primary hydraulic fracture and the diversion of the fluid into secondary and tertiary fractures are clearly indentified and quantified. The paper indicates how safe, secured and controlled injection in shale can be achieved, as opposed to the unconfined cases of the early history on the Norwegian Continental Shelf. It also shows that while maintaining safety and vertical-confinement, massive increase of permeability of nano-Darcy shale rock-masses can be achieved. Both results are extremely important when it comes to cuttings injection in shale. Even more importantly, the paper discusses the implications of these results to the hydraulic stimulation of shale reservoirs in terms of both safety and efficiency. First, the permeability increases observed during cutting re-injection in the Ekofisk area can be set as realistically-achievable goals during shale reservoir stimulation.Second, the identification of the mechanisms having led to this development can be used to adapt current stimulation techniques to reach such permeability-increase goals.Finally, the techniques presented in the paper can be used to ensure the vertical confinement of future stimulation jobs.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.030
GPT teacher head0.281
Teacher spread0.251 · 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 designObservational
Domainnot available
GenreReview

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

Citations3
Published2014
Admission routes1
Has abstractyes

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