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Record W2955968138 · doi:10.2118/197048-pa

Integrated Interpretation of Microseismic and Petroleum-Engineering Data for Comparison of Gas Production in Two Interfering Adjacent Wellpads in the Horn River Basin, Canada

2019· article· en· W2955968138 on OpenAlexaffabout
Abdolnaser Yousefzadeh, Qi Li, Roberto Aguilera, Claudio Virués

Bibliographic record

VenueSPE Production & Operations · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsNexen (Canada)University of Calgary
Fundersnot available
KeywordsMicroseismGeologyOil shaleSeismologyStructural basinMineralogyPetrologyGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

Summary We present an integrated interpretation of microseismic, treatment, and production data from hydraulic-fracturing jobs carried out in two adjacent wellpads in the Horn River Basin, northeast British Columbia, Canada. We conclude that poor correlation coefficients (R2) in crossplots of normalized production rate vs. the product of stimulated reservoir volume (SRV) and porosity and total organic carbon (TOC) (SRV×ϕ×TOC) indicate pressure interference between wells or wellpads. Good correlation coefficients in the same crossplots indicate lack of interference. The SRV×ϕ×TOC product reflects the hydrocarbon pore SRV because there is a relationship between TOC and hydrocarbon saturation in shales (Lopez and Aguilera 2018). Our results suggest that natural-fracture networks have an important effect on well connectivity and on the spatial distribution of microseismic data. Connectivity between wellpads occurs through a network of pre-existing natural fractures, which are approximately perpendicular to the least principal compressive stress in the area. This conclusion is supported by data analysis from Wellpads I and II in the Horn River Basin. Wellpad I includes eight wells that were drilled and fractured in the Muskwa and Otter Park formations (four wells in each formation) in 2010. Wellpad II includes three wells drilled and fractured in 2011 in each of the three shale formations, Muskwa, Otter Park, and Evie. There is a 1-year interval between fracturing on the first and second wellpads. The data analysis includes evaluation of magnitudes, b-values, moment-tensor inversion (MTI), and the spatial and temporal distributions of three-component microseismic events recorded during more than 200 stages of fracturing by multiwell downhole arrays. We analyzed Gutenberg-Richter frequency/magnitude graphs for each fracturing stage, and with proper integration of b-values, fracture-complexity index (FCI), MTI information, and treatment data, we distinguished hydraulic-fracturing-related events and events associated with slip along the surface of natural fractures. The results are compared with 5- and 4-year gas-production data in Wellpads I and II, respectively. Identification of natural fractures and information about interactions between hydraulically fractured wells are both essential for optimal well placement and completion, reservoir characterization, SRV calculation, and reservoir simulation. This study presents a distinctive insight into the integrated interpretation of microseismic events and production data to identify the activation of natural fractures and interference between the hydraulically fractured wells. The methodology developed in this study is thus related to production engineering, but examines it from the point of view of microseismic data.

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 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 score0.139
Threshold uncertainty score0.977

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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2019
Admission routes2
Has abstractyes

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