Identification of flow units using methods of Testerman statistical zonation, flow zone index, and cluster analysis in Tabnaak gas field

Mahjour, Seyed Kourosh; Alaskari, M K Ghasem; Masihi, Mohsen

doi:10.1007/s13202-015-0224-4

Cited by 34 publications

(18 citation statements)

References 12 publications

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“…The cumulative percentage of flow vs. storage capacities were plotted to obtain a curve. The slope or the points of the inflexions were then interpreted preliminarily to represent various FU intervals, whether they are efficiency zones, baffle or barrier units (Chopra et al 1987;Newsham and Rushing 2001;Gomes et al 2008;Mahjour et al 2016).…”

Section: Methodsmentioning

confidence: 99%

Determination of Reservoir Flow Units from Core Data: A Case Study of the Lower Cretaceous Sandstone Reservoirs, Western Bredasdorp Basin Offshore in South Africa

2020

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The overarching aim of this study is to use core measurements of porosity and permeability in three wells (MO1, MO2, and MO3) to generate a scheme of sandstone reservoir zonation for identification of flow units in the E-M gas field of the Western Bredasdorp Basin Offshore in South Africa. The evaluation method began by establishing rock types within a geological framework that allowed the definition of five facies, grouped as facies A, B, C, D, and E. Facies A was recognized as the best petrophysical rock type. In contrast, facies E was recognized as impervious rock. The results of independent reservoir classification methods were integrated to identify flow zones that yielded positive results. The results ultimately culminated in a zonation scheme for the Basin. Twelve flow zones were identified and were broadly classified as high, moderate, low, very low, and tight zones. The high zone was characterized by pore throat radius of ‡ 10 lm, flow zone index (FZI) of ‡ 5.0 lm, and flow unit efficiency (FUE) of ‡ 0.8. In contrast, very low efficiency zones had pore throat radius and FZI of < 2 lm, and FUE of £ 0.2. The high-efficiency zones were comparable to facies A and the tight zone to facies E. Facie C provided sand-sand contacts that allowed flow between the zones. One high, two moderate, four low, and five very low efficiency zones were identified. The plot of FUE can be compared directly with flowmeter logs. The results obtained from this study will serve as an input parameter for reservoir studies in the western Bredasdorp Basin.

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Section: Methodsmentioning

confidence: 99%

Determination of Reservoir Flow Units from Core Data: A Case Study of the Lower Cretaceous Sandstone Reservoirs, Western Bredasdorp Basin Offshore in South Africa

2020

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“…Identification of permeability is of major importance to identify productive flow zones in a geothermal aquifer (Mahjour et al 2016). Permeability is a rock property that is directly linked to pore size and effective porosity and varies widely in heterogeneous carbonate deposits from < 0.01 millidarcy (mD) to well over 1 Darcy (Lucia 2007).…”

Section: Permeabilitymentioning

confidence: 99%

Porosity–permeability relationship derived from Upper Jurassic carbonate rock cores to assess the regional hydraulic matrix properties of the Malm reservoir in the South German Molasse Basin

Bohnsack¹,

Potten²,

Pfrang³

et al. 2020

Geotherm Energy

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For the successful realization and productivity prediction of new hydrothermal projects in the South German Molasse Basin, the hydraulic matrix properties of the Upper Jurassic Malm reservoir have to be determined as accurately as possible. To obtain specific information on the distribution of the petrophysical parameters (e.g., rock density, porosity, and permeability) 363 samples of rare drilling cores from the reservoir northeast of Munich (wells Moosburg SC4 and Dingolfing FB) were investigated using different experimental methods. Additionally, porosity was calculated by a downhole resistivity log of a nearby borehole close to Munich for comparison and the attempt of transferability of the data set to other locations within the Central Molasse Basin. Core data were divided into groups of different stratigraphic and petrographic units to cover the heterogeneity of the carbonate aquifer and provide data ranges to improve reservoir and prediction models. Data for effective porosity show a high variance from 0.3 to 19.2% throughout this heterogeneous aquifer. Permeability measured on core samples is scattered over several orders of magnitude (10 −4-10 2 mD). Permeability models based on the porosity-permeability relationship were used to estimate permeability for the whole aquifer section and identify possible flow zones. A newly developed empirical model based on distinct lithofacies types allows a permeability estimation with a deviation < 10 mD. However, fractured, karstified, and vuggy zones occurring in this typically karstified, fractured, and porous reservoir cannot yet be taken into account by the model and result in an underestimation of permeability on reservoir scale. Overall, the dominant permeability trends can be mapped well using this model. For the regional transfer and the correlation of the results, a core-related porosity/ permeability log for the reservoir was compiled for a well close to Munich showing similarities to the core investigations. The validation of the regional transferability of the parameter set to other locations in the Molasse Basin was carried out by correlation with the interpreted log data of a well near Munich.

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“…This technique mostly helps to divide a ''pile'' of information into the meaningful groups based on the group's similarity. These obtained groups are internally homogeneous and externally heterogeneous (Mahjour et al, 2016;Stinco et al, 2001). The base of clustering method is the distance between two data objects in one matrix to measure the similarity of data.…”

Section: Identification Of Flow Units Using Hca Methodsmentioning

confidence: 99%

“…Aminian et al (2003) delivered a neural network technique to determine flow unit types and predict the petrophysical parameters in the reservoir. Mahjour et al (2016), made a comparison of different methods to identify flow units in the Tabnak gas field in southern Iran. They concluded that Hierarchical Cluster Analysis (HCA) is more efficient than the other methods used for the general assessment of flow units in field scale.…”

Section: Introductionmentioning

confidence: 99%

Developing a workflow to represent fractured carbonate reservoirs for simulation models under uncertainties based on flow unit concept

Mahjour

Correia

Santos

et al. 2019

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

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Description of fractured reservoir rock under uncertainties in a 3D model and integration with reservoir simulation is still a challenging topic. In particular, mapping the potential zones with a reservoir quality can be very useful for making decisions and support development planning. This mapping can be done through the concept of flow units. In this paper, an integrated approach including a Hierarchical Cluster Analysis (HCA), geostatistical modeling and uncertainty analysis is developed and applied to a fractured carbonate in order to integrate on numerical simulation. The workflow begins with different HCA methods, performed to well-logs in three wells, to identify flow units and rock types. Geostatistical techniques are then applied to extend the flow units, petrophysical properties and fractures into the inter-well area. Finally, uncertainty analysis is applied to combine different types of uncertainties for generating ensemble reservoir simulation models. The obtained clusters from different HCA methods are evaluated by the cophenetic coefficient, correlation coefficient, and variation coefficient, and the most appropriate clustering method is used to identify flow units for geostatistical modeling. We subsequently define uncertainties for static and dynamic properties such as permeability, porosity, net-to-gross, fracture, water-relative permeability, fluid properties, and rock compressibility. Discretized Latin Hypercube with Geostatistical (DLHG) method is applied to combine the defined uncertainties and create an ensemble of 200 simulation models which can span the uncertainty space. Eventually, a base production strategy is defined under operational conditions to check the consistency and reliability of the models created with UNISIM-II-R (reference model) as a real reservoir with known results. Results represent the compatibility of the methodology to characterize fractured reservoirs since those models are consistent with the reference model (used to generate the simulation models). The proposed workflow provides an efficient and useful means of supporting development planning under uncertainty.

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Identification of flow units using methods of Testerman statistical zonation, flow zone index, and cluster analysis in Tabnaak gas field

Cited by 34 publications

References 12 publications

Determination of Reservoir Flow Units from Core Data: A Case Study of the Lower Cretaceous Sandstone Reservoirs, Western Bredasdorp Basin Offshore in South Africa

Determination of Reservoir Flow Units from Core Data: A Case Study of the Lower Cretaceous Sandstone Reservoirs, Western Bredasdorp Basin Offshore in South Africa

Porosity–permeability relationship derived from Upper Jurassic carbonate rock cores to assess the regional hydraulic matrix properties of the Malm reservoir in the South German Molasse Basin

Developing a workflow to represent fractured carbonate reservoirs for simulation models under uncertainties based on flow unit concept

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