The Estimation of Filtration Reservoir Properties with Log Data

2012 ◽  
Author(s):  
Dmitry Kozhevnikov ◽  
Kazimir Kovalenko ◽  
Ivan Deshenenkov ◽  
Alexander Nikolaevich Petrov
2017 ◽  
Vol 5 (1) ◽  
pp. 37 ◽  
Author(s):  
Inyang Namdie ◽  
Idara Akpabio ◽  
Agbasi Okechukwu .E.

Bonga oil field is located 120km (75mi) southeast of the Niger Delta, Nigeria. It is a subsea type development located about 3500ft water depth and has produced over 330 mmstb of hydrocarbon till date with over 16 oil producing and water injection wells. The producing formation is the Middle to Late Miocene unconsolidated turbidite sandstones with lateral and vertical homogeneities in reservoir properties. This work, analysis the petrophysical properties of the reservoir units for the purpose of modeling the effect of shale content on permeability in the reservoir. Turbidite sandstones are identified by gamma-ray log signatures as intervals with 26-50 API, while sonic, neutron, resistivity, caliper and other log data are applied to estimate volume of shale ranging between 0.972 v/v for shale intervals and 0.0549 v/v for turbidite sands, water saturation of 0.34 v/v average in most sand intervals, porosity range from 0.010 for shale intervals to 0.49 v/v for clean sands and permeability values for the send interval 11.46 to2634mD, for intervals between 7100 to 9100 ft., Data were analyzed using the Interactive Petrophysical software that splits the whole curve into sand and shale zones and estimates among other petrophysical parameters the shale contents of the prospective zones. While Seismic data revealed reservoir thickness ranging from 25ft to over 140ft well log data within the five wells have identified sands of similar thickness and estimated average permeability of700mD. Within the sand units across the five wells, cross plots of estimated porosity, volume of shale and permeability values reveal strong dependence of permeability on shale volume and a general decrease in permeability in intervals with shale volume. It is concluded that sand units with high shale contents that are from0.500 to0.900v/v will not provide good quality reservoir in the field.


2021 ◽  
Vol 11 (2) ◽  
pp. 601-615
Author(s):  
Tokunbo Sanmi Fagbemigun ◽  
Michael Ayu Ayuk ◽  
Olufemi Enitan Oyanameh ◽  
Opeyemi Joshua Akinrinade ◽  
Joel Olayide Amosun ◽  
...  

AbstractOtan-Ile field, located in the transition zone Niger Delta, is characterized by complex structural deformation and faulting which lead to high uncertainties of reservoir properties. These high uncertainties greatly affect the exploration and development of the Otan-Ile field, and thus require proper characterization. Reservoir characterization requires integration of different data such as seismic and well log data, which are used to develop proper reservoir model. Therefore, the objective of this study is to characterize the reservoir sand bodies across the Otan-Ile field and to evaluate the petrophysical parameters using 3-dimension seismic and well log data from four wells. Reservoir sands were delineated using combination of resistivity and gamma ray logs. The estimation of reservoir properties, such as gross thickness, net thickness, volume of shale, porosity, water saturation and hydrocarbon saturation, were done using standard equations. Two horizons (T and U) as well as major and minor faults were mapped across the ‘Otan-Ile’ field. The results show that the average net thickness, volume of shale, porosity, hydrocarbon saturation and permeability across the field are 28.19 m, 15%, 37%, 71% and 26,740.24 md respectively. Two major faults (F1 and F5) dipping in northeastern and northwestern direction were identified. The horizons were characterized by structural closures which can accommodate hydrocarbon were identified. Amplitude maps superimposed on depth-structure map also validate the hydrocarbon potential of the closures on it. This study shows that the integration of 3D seismic and well log data with seismic attribute is a good tool for proper hydrocarbon reservoir characterization.


2008 ◽  
Vol 15 ◽  
pp. 17-20 ◽  
Author(s):  
Tanni Abramovitz

More than 80% of the present-day oil and gas production in the Danish part of the North Sea is extracted from fields with chalk reservoirs of late Cretaceous (Maastrichtian) and early Paleocene (Danian) ages (Fig. 1). Seismic reflection and in- version data play a fundamental role in mapping and characterisation of intra-chalk structures and reservoir properties of the Chalk Group in the North Sea. The aim of seismic inversion is to transform seismic reflection data into quantitative rock properties such as acoustic impedance (AI) that provides information on reservoir properties enabling identification of porosity anomalies that may constitute potential reservoir compartments. Petrophysical analyses of well log data have shown a relationship between AI and porosity. Hence, AI variations can be transformed into porosity variations and used to support detailed interpretations of porous chalk units of possible reservoir quality. This paper presents an example of how the chalk team at the Geological Survey of Denmark and Greenland (GEUS) integrates geological, geophysical and petrophysical information, such as core data, well log data, seismic 3-D reflection and AI data, when assessing the hydrocarbon prospectivity of chalk fields.


2010 ◽  
Author(s):  
Mohamed Sitouah ◽  
Gabor Korvin ◽  
Abdulatif Al-Shuhail ◽  
Osman MAbdullatif ◽  
Abdulazeez Abdulraheem ◽  
...  

2020 ◽  
Vol 39 (3) ◽  
pp. 170-175
Author(s):  
Islam A. Mohamed ◽  
Adel Othman ◽  
Mohamed Fathy

In highly heterogeneous basins with complex subsurface geology, such as the Nile Delta Basin, accurate prediction of reservoir modeling has been a challenge. Reservoir modeling is a continuous process that begins with field discovery and ends with the last phases of production and abandonment. Currently, the stochastic reservoir modeling method is widely used instead of the traditional deterministic modeling method to consider spatial statistics and uncertainties. However, the modeling workflow is demanding and slow, typically requiring months from the initial model concept to flow simulation. In addition, errors from early model stages become cumulative and are difficult to change retroactively. To overcome these limitations, a new workflow is proposed that implements probabilistic neural network inversion to predict reservoir properties. First, well-log data were conditioned properly to match the seismic data scale. Then, the networks were trained and validated, using the conditioned well-log data and seismic internal/external attributes, to predict water saturation and effective porosity 3D volumes. The resulting volumes were sampled in simulation 3D grids and tested using a blind well test. Subsequently, the permeability was calculated from a porosity-permeability relationship inside the reservoir. Finally, a dynamic simulation project of the field was performed in which the historical field production and pressures were compared to the predicted values. One of the Pliocene deepwater turbidite reservoirs in the offshore Nile Delta was used to demonstrate the proposed approach. The results proved the accuracy of the model in predicting the reservoir properties and honoring the heterogeneity of the reservoir. The new approach represents a shortcut for the seismic-to-simulation process, providing a reliable and fast way of constructing a reservoir model and making the seismic-to-simulation process easier.


2021 ◽  
Vol 11 (7) ◽  
pp. 2911
Author(s):  
Naveed Ahmad ◽  
Sikandar Khan ◽  
Abdullatif Al-Shuhail

Well logging is a significant procedure that assists geophysicists and geologists with making predictions regarding boreholes and efficiently utilizing and optimizing the drilling process. The current study area is positioned in the Punjab Territory of Pakistan, and the geographic coordinates are 30020′10 N and 70043′30 E. The objective of the current research work was to interpret the subsurface structure and reservoir characteristics of the Kabirwala area Tola (01) well, which is located in the Punjab platform, Central Indus Basin, utilizing 2D seismic and well log data. Formation evaluation for hydrocarbon potential using the reservoir properties is performed in this study. For the marked zone of interest, the study also focuses on evaluating the average water saturation, average total porosity, average effective porosity, and net pay thickness. The results of the study show a spotted horizon stone with respect to time and depth as follows: Dunghan formation, 0.9 s and 1080.46 m; Cretaceous Samana Suk formation, 0.96 s and 1174.05 m; Datta formation, 1.08 s and 1400 m; and Warcha formation, 1.24 s and 1810 m. Based on the interpretation of well logs, the purpose of petrophysical analysis was to identify hydrocarbon-bearing zones in the study area. Gamma ray, spontaneous potential, resistivity, neutron, and density log data were utilized. The high zone present in the east–west part of the contour maps may be a possible location of hydrocarbon entrapment, which is further confirmed by the presence of the Tola-01 well.


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