Comparison of Asmari, Pabdeh and Gurpi formation's fractures, derived from image log

Khoshbakht, F.; Memarian, Hossein; Mohammadnia, Mohammad

doi:10.1016/j.petrol.2009.02.011

Cited by 100 publications

(45 citation statements)

References 4 publications

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“…Alavi (2004) collects all lithostratigraphic units of the Zagros fold-thrust belt data and published the perfect description of formations. Asmari (Oligocene to lowermost Miocene), medium-bedded to thick-bedded, locally shelly or oolitic, nummulites-bearing limestones (grainstone, packstone, wackestone) shoaling upward above a thin basal conglomerate from fine-grained (low-energy) deep-marine marly limestone to high-energy shallow-marine skeletal grainstone; composed of a number of sequences; a unconformity-bounded, highly prolific reservoir; interpreted as transgressive-regressive foredeep facies of the proforeland basin (Khoshbakht et al, 2009).…”

Section: Field Descriptionmentioning

confidence: 99%

“…When fractures are open, they act as pathways for hydrocarbon production and may even transform a very low permeability reservoir into highly productive zones. When cemented they act as barriers to hydrocarbon flow hindering the motion of hydrocarbon toward the wells (Haller and Porturas, 1998;Khoshbakht et al, 2009). Therefore in modeling fractured reservoirs, understanding fracture properties is very important.…”

Section: Introductionmentioning

confidence: 99%

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Integration of Adaptive Neuro-Fuzzy Inference System, Neural Networks and Geostatistical Methods for Fracture Density Modeling

Jafari

Kadkhodaie

Sharghi

et al. 2013

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Résumé -Intégration de système d'inférence adaptative de neurone flou (ANFIS), de réseaux de neurones (NN) et de méthodes géostatistiques pour la modélisation de la densité de fractures -Les images de diagraphies fournissent des informations utiles pour l'étude de fractures dans des réservoirs naturellement fracturés. L'inclinaison, l'azimut, l'ouverture et la densité de fractures peuvent être obtenus à partir des images de diagraphies et ces éléments ont une grande importance dans la caractérisation des réservoirs naturellement fracturés. L'imagerie de toutes les parties fracturées des réservoirs d'hydrocarbures et l'interprétation des résultats sont des processus longs et coûteux. Dans cette étude, une méthode améliorée pour faire une corrélation quantitative entre les densités de fractures obtenues à partir des images de diagraphies et de données conventionnelles, a été proposée par l'intégration des différents systèmes d'intelligence artificielle. Pour l'estimation globale de la densité de fractures à partir de données de diagraphies conventionnelles, la méthode proposée combine les résultats obtenus à partir d'algorithmes du système d'inférence adaptative flou de neurones (ANFIS) et du réseau de neurones (NN). Une méthode simple de moyenne a été utilisée pour obtenir un meilleur résultat en combinant les résultats de l'ANFIS et NN. L'algorithme a été appliqué à d'autres puits du champ pour obtenir la densité de fracture. Afin de modéliser la densité de fractures dans le réservoir, nous avons utilisé des algorithmes de simulation et de variographie séquentiels comme la Simulation à Indicateurs Séquentiels (SIS) et la Simulation Gaussienne Tronquée (TGS). L'algorithme global a été appliqué au réservoir d'Asmari de l'un des champs pétroliers du sud-ouest iranien. L'analyse de l'histogramme a été appliquée au contrôle de la qualité des modèles obtenus. Les résultats de cette étude montrent que pour nombre plus élevé de fractures, l'algorithme de faciès TGS fonctionne mieux que le SIS, mais que pour un petit nombre de faciès de fractures les deux algorithmes fournissent des résultats à peu près identiques. Abstract

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Section: Field Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integration of Adaptive Neuro-Fuzzy Inference System, Neural Networks and Geostatistical Methods for Fracture Density Modeling

Jafari

Kadkhodaie

Sharghi

et al. 2013

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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“…FMI is an image log providing high resolution images from the wellbore which are obtained based on the electrical resistivity difference existing among different layers (Khoshbakht et al 2009;Rajabi et al 2010). This enables geologists to distinguish small scale phenomena in the wellbore which can be used to help dramatically the field development studies (SUN et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Drilling fluid loss control via implementing the FMI and DSI logs to protect environment

Shalafi

Moradi

GhassemAlaskari

et al. 2016

Model. Earth Syst. Environ.

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Implementing the drilling fluids in drilling operations is of paramount importance owing to the variety of applications and benefits they provide. Materials added to drilling fluid could cause numerous environmental problems in soil and water resources, and these problems are more pronounced in offshore as compared to land fields. Heavy metals such as mercury, barium, arsenic, lead, and nickel exist in drilling fluid, which bring detrimental damages to the environment. Moreover, heavy metals exist in oil-based muds due to presence of oil where their nickel and vanadium are much greater than other heavy metals. Additive materials and heavy metals existing in drilling fluid could pose irreparable environmental damage if fluid loss into the formation occurs. Regarding to the fact that drilling fluid loss occurs via the open fractures in the wellbore, the main aim of this study is to evaluation of wellbore fractures via implementing the FMI log and fracturing pressure using the slowness of compressional and shear waves. A total of 61 fractures in Dalan formation and 72 fractures in Kangan formation are interpreted and fracturing pressure for these formations, ranges between 8400 and 9450 psi. Implementing the results obtained from this study, drilling fluid loss into the formation and subsequent environmental damage could be prohibited via controlling the pumping pressure and density variation of drilling fluid in accordance with the formation fracturing pressure.

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“…Image logs and cores are the best methods for the analysis of reservoir parameters. However, cores have serious limitations such as high cost, low recovery in fractured interval, and changing core orientation during coring [Khoshbakht et al, 2009;Mohebbi et al, 2007]. The Asmari Formation (Oligo-Miocene) is a main petroleum reservoir of Iran.…”

Section: Introductionmentioning

confidence: 99%

“…Petroleum production potential of the Asmari reservoir is about 85% of the crude oil due to abnormal vuggy porosity type resulted from natural fractures [Gholipour, 1998]. Therefore the study of the fractures in the Asmari reservoir is a serious subject up to now [Aghli, 2013;Khoshbakht et al, 2009Khoshbakht et al, , 2012. It is cleared that fracture study and evaluation in any oilfield can be helpful in the complementary stage of the well, the determination of perforating depth, field development, directional drilling well program, fluid injection zone and fracture modeling.…”

Section: Introductionmentioning

confidence: 99%

Lithology effects on the fractures parameters using image log and petrophysical data

Soleimani¹,

Amiri²,

Samani³

et al. 2016

Russ. J. Earth Sci.

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Fractures within a reservoir play an influential role in the porosity and permeability, therefore affect the fluid flow. By analyzing properties of fractures, such as fracture height, density and mutually spacing and compare them with different tectonic locations and different lithologies, one could gain insight in the mechanical behavior of a rock mass, when distorted by tectonic forces. The velocity deviation log (VDL) can be used for determination of effective porosity. The result indicated that there is a high fractures density in the Asmari Formation which shows high correlation with VDL. They are mainly strike N75E, S75W direction and are chiefly observed in the upper Asmari zones. Fractures and vuggy have been also observed in the well. Image log showed a range of bedding dip from 53-89 degree with strike N55W, S55E in the well indicating of reverse limb in the field. Image log show tow set fracture which azimuth 347 for discontinuous fracture and 220 with strike N55W, S55E for continuous fracture. Main type of lithology determined by petrophysical log showed that dolomite is dominant constituent. Induced fractures and breakouts haven't seen observed in this well. After correlating image logs with VDL and lithology, zones with dominant pure dolomite presented higher aperture rather zones with dolomite and anhydrite. Fracture density is more affected by bed thickness to mineralogy. Zones with negative deviation velocity have high fracture density or high fracture aperture.

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Comparison of Asmari, Pabdeh and Gurpi formation's fractures, derived from image log

Cited by 100 publications

References 4 publications

Integration of Adaptive Neuro-Fuzzy Inference System, Neural Networks and Geostatistical Methods for Fracture Density Modeling

Integration of Adaptive Neuro-Fuzzy Inference System, Neural Networks and Geostatistical Methods for Fracture Density Modeling

Drilling fluid loss control via implementing the FMI and DSI logs to protect environment

Lithology effects on the fractures parameters using image log and petrophysical data

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