Genetic mechanism and development of the unsteady Sarvak play of the Azadegan oil field, southwest of Iran

Du, Yang; Chen, Jie; Cui, Yi; Jun, Xin; Wang, Juan; Li, Yi-Zhen; Fu, Xiao

doi:10.1007/s12182-016-0077-6

Cited by 33 publications

(10 citation statements)

References 25 publications

(51 reference statements)

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“…It represents a rim of the carbonate platform, or a belt of shelf margin, associated with the random distribution of the rudist reefal mound, which clearly appears in the region A with a high thickness in the vicinity of the productive well Dujail-1, where it is the preferential place for reef growth. This confirms that the distribution and thickness of the rudist buildup are controlled by paleo-high features on the rim belt of the carbonate platform [20].  In the east and southeast parts of the study area, the thickness is decreasing to less than 250m, which may represent a deep basin.…”

Section: Isopach Map Of Mishrif Formationsupporting

confidence: 78%

Predicting the Depositional Environments of Mishrif Formation from Seismic Isopach Map in the Dujaila Oil Field, Southeast-Iraq

Khawaja

Thabit

2021

eijs

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In this paper, we attempt to predict the depositional environments with associated lithofacies of the main reservoir of the late Cretaceous Mishrif carbonate Formation, depending on the analysis of the created seismic isopach map by integrating seismic and well data. The isopach map was created from a 3D-seismic reflection survey carried out at the Dujaila oil field in southeastern Iraq, which is of an area of 602.26 Km2, and integrated with the data of the two explored wells. Based on the interpretation of the seismic isopach map, the diagram of the 3D-depositional environment model of Mishrif Formation was constructed. It showed three distinguished depositional environments, which were graduated from a back reef lithofacies of a shallow open marine (shelf) environment in the west and NW, to a shoal environment of isolated Rudist reefal buildup in the middle, and a fore reef lithofacies of the deep open marine basin environment in the SE of the field. A 3D-instantaneous frequency model was generated to verify the capability of the seismic isopach map of predicting the depositional environments, which in turn showed that the low frequency was restricted in the region of the high thickness of Rudist reefal buildups (porous reservoir facies) in the vicinity of the productive well Dujaila-1.

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Section: Isopach Map Of Mishrif Formationsupporting

confidence: 78%

Predicting the Depositional Environments of Mishrif Formation from Seismic Isopach Map in the Dujaila Oil Field, Southeast-Iraq

Khawaja

Thabit

2021

eijs

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“…2 Map). It produces oil mainly from the Upper Cretaceous, Sarvak carbonate, reservoirs located at about 2700 m below surface (Du et al 2016). However, there other oil-bearing reservoirs and permeable zones present in the field (Fig.…”

Section: Dataset Descriptionmentioning

confidence: 99%

“…3) linked to a prolific petroleum system (Liu et al 2013). The field consists of a large domal structure with two crestal points (north and south) with the oil water contact sloping from south to north across the southern crestal portion of the field (Du et al 2016). There are four oil producing zones within the Sarvak reservoir, of which the S-3 zone is the most prolific producer and reserves holder.…”

Section: Dataset Descriptionmentioning

confidence: 99%

Effective prediction of lost circulation from multiple drilling variables: a class imbalance problem for machine and deep learning algorithms

Wood

Mardanirad

Zakeri³

2021

J Petrol Explor Prod Technol

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Multiple machine learning (ML) and deep learning (DL) models are evaluated and their prediction performance compared in classifying five wellbore fluid-loss classes from a 20-well drilling dataset (Azadegan oil field, Iran). That dataset includes 65,376 data records with seventeen drilling variables. The dataset fluid-loss classes are heavily imbalanced (> 95% of data records belong to the less significant loss classes 1 and 2; only 0.05% of the data records belong to the complete-loss class 5). Class imbalance and the lack of high correlations between the drilling variables and fluid-loss classes pose challenges for ML/DL models. Tree-based and data matching ML algorithms outperform DL and regression-based ML algorithms in predicting the fluid-loss classes. Random forest (RF), after training and testing, makes only 35 prediction errors for all data records. Consideration of precision recall and F1-scores and expanded confusion matrices show that the RF model provides the best predictions for fluid-loss classes 1 to 3, but that for class 4 Adaboost (ADA) and class 5 decision tree (DT) outperform RF. This suggests that an ensemble of the fast to execute RF, ADA and DT models may be the best way to practically achieve reliable wellbore fluid-loss predictions. DL models underperform several ML models evaluated and are particularly poor at predicting the least represented classes 4 and 5. The DL models also require much longer execution times than the ML models, making them less attractive for field operations that require prompt information regarding rapid real-time decision responses to pending class-4 and class-5 fluid-loss events.

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“…The Kazhdumi Formation in the Yadavaran Oilfield of Iran is mainly composed of dark asphalt shale and gray limestone, in which asphalt heavy oil is extensively developed (Du et al., 2016; Rafieepour and Jalalifar, 2014). During the drilling process, the pore pressure of the formation fluctuates greatly, and asphalt spillage increases instead of decreasing when the density of drilling fluid goes up (Lu et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Liquid–liquid gravity displacement in a vertical fracture during drilling: Experimental study and mathematical model

Xiao

Meng

Zhang

et al. 2019

Energy Exploration & Exploitation

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Gravity displacement often occurs when drilling a vertical fractured formation, causing a downhole complexity with risk of blowout and reservoir damage, well control difficulty, drilling cycle prolongation, and increased costs. Based on an experimental device created for simulating the gravity displacement, various factors affecting the displacement quantity were quantitatively evaluated by simulating the fracture width, asphalt viscosity, drilling fluid density, and viscosity under different working conditions, and a liquid–liquid displacement law was obtained. Using the theories of rock mechanics, fluid mechanics, and seepage mechanics, based on conformal mapping, as well as a fracture-pore double substrate fluid flow model, we established a steady-state mathematical model of fractured formation liquid–liquid gravity displacement by optimizing the shape factors and using a combination of gravity displacement experiments to verify the feasibility of the mathematical model. We analyzed the influence of drilling fluid density, fracture height and length, and asphalt viscosity on displacement rate, and obtained the corresponding laws. The results show that when the oil–fluid interface is stable, the fracture width is the most important factor affecting the gravity displacement, and plugging is the most effective means of managing gravity displacement.

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Genetic mechanism and development of the unsteady Sarvak play of the Azadegan oil field, southwest of Iran

Cited by 33 publications

References 25 publications

Predicting the Depositional Environments of Mishrif Formation from Seismic Isopach Map in the Dujaila Oil Field, Southeast-Iraq

Predicting the Depositional Environments of Mishrif Formation from Seismic Isopach Map in the Dujaila Oil Field, Southeast-Iraq

Effective prediction of lost circulation from multiple drilling variables: a class imbalance problem for machine and deep learning algorithms

Liquid–liquid gravity displacement in a vertical fracture during drilling: Experimental study and mathematical model

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