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Enregistrement W2063090922 · doi:10.7842/kigas.2013.17.4.58

Study on Production Performance of Shale Gas Reservoir using Production Data Analysis

2013· article· en· W2063090922 sur OpenAlexaboutno aff
Chang-Hoon Sin, Sunil Kwon

Notice bibliographique

RevueJournal of the Korean Institute of Gas · 2013
Typearticle
Langueen
DomaineEngineering
ThématiqueReservoir Engineering and Simulation Methods
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSuperposition principleOverburdenPermeability (electromagnetism)Production (economics)Oil shaleFlow (mathematics)Hydrology (agriculture)Petroleum engineeringMaterial balanceShale gasVolume (thermodynamics)ExponentSoil scienceEnvironmental scienceGeologyMathematicsGeotechnical engineeringChemistryPhysicsGeometryEngineering

Résumé

récupéré en direct d'OpenAlex

본 연구에서는 캐나다 셰일가스전에 위치한 2개의 생산정에 대해 생산특성에 따라 적절한 생산자료 분석기법을 이용하여 분석을 수행하였다. Case A 생산정의 경우 생산자료가 매우 가변적으로 나타나 시간과 중첩시간을 적용하여 비교분석을 실시하였다. 유동영역을 구분하기 위해 생산자료를 로그-로그 그래프에 도시한 결과 천이유동구간만 나타났다. 시간과 중첩시간을 적용하여 자극을 받은 저류층 면적이 각각 180, 240 acres로 산출되었고, 원시가스부존량은 15, 20 Bscf로 계산되었다. 그러나 산출된 저류층 면적은 경계영향유동자료로부터 산출된 것이 아니기 때문에 최소 값으로 판단된다. 이에 저류층 면적과 감퇴지수에 대한 생산성 예측을 수행하였다. 그 결과 감퇴지수가 0.5, 1로 커질수록 궁극가채량이 1.2배와 1.4배로 증가하였다. 또한 저류층 면적이 240에서 360 acres로 커지면 궁극가채량이 1.3배 증가되는 것을 확인할 수 있었다. Case B의 고압 저류층에 위치한 생산정은 상부지층압에 따른 지층압축률과 투과도를 적용하여 분석하였다. 지역학적 영향을 적용한 경우와 아닌 경우를 비교한 결과, 저류층 면적은 1.4배, 원시가스부존량이 1.5배로 증가하였다. 셰일 가스전 현장자료에 대한 분석 결과, 분석 방법에 따라 원시가스부존량, 궁극가채량 등 향후 생산성 예측이 크게 달라지므로 생산자료에 따라 유사시간, 중첩시간, 지역학적 분석 등의 적절한 분석방법을 적용하여야 정확한 생산자료 분석이 가능할 것으로 판단된다. This paper presents production data analysis for two production wells located in the shale gas field, Canada, with the proper analysis method according to each production performance characteristics. In the case A production well, the analysis was performed by applying both time and superposition time because the production history has high variation. Firstly, the flow regimes were classified with a log-log plot, and as a result, only the transient flow was appeared. Then the area of simulated reservoir volume (SRV) analyzed based on flowing material balance plot was calculated to 180 acres of time, and 240 acres of superposition time. And the original gas in place (OGIP) also was estimated to 15, 20 Bscf, respectively. However, as the area of SRV was not analyzed with the boundary dominated flow data, it was regarded as the minimum one. Therefore, the production forecasting was conducted according to variation of b exponent and the area of SRV. As a result, estimated ultimate recovery (EUR) increased 1.2 and 1.4 times respectively depending on b exponent, which was 0.5 and 1. In addition, as the area of SRV increased from 240 to 360 acres, EUR increased 1.3 times. In the case B production well, the formation compressibility and permeability depending on the overburden were applied to the analysis of the overpressured reservoir. In comparison of the case that applied geomechanical factors and the case that did not, the area of SRV was increased 1.4 times, OGIP was increased 1.5 times respectively. As a result of analysis, the prediction of future productivity including OGIP and EUR may be quite different depending on the analysis method. Thus, it was found that proper analysis methods, such as pseudo-time, superposition time, geomechanical factors, need to be applied depending on the production data to gain accurate results.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,139
Score d'incertitude au seuil0,348

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,076
Tête enseignante GPT0,310
Écart entre enseignants0,234 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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