Fully Integrated 3D-Reservoir Characterization and Flow Simulation Study: A Field Case Example

Al-Deeb, Maged; Bloch, Gérard; El-Abd, Salem; Charfeddine, Mohsen; Bahar, Asnul; Ates, Harun; Soeriawinata, T.; Kelkar, Mohan

doi:10.2118/78510-ms

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…These realizations were then ranked and upscaled using streamline simulation as explained below. Subsequently, three realizations were selected and history matched successfully with minimal adjustments 11 .…”

Section: Reservoir Modelmentioning

confidence: 99%

Ranking and Upscaling of Geostatistical Reservoir Models by Use of Streamline Simulation: A Field Case Study

Ates¹,

Bahar²,

Salem

et al. 2005

SPE Reservoir Evaluation &Amp; Engineering

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Section: Reservoir Modelmentioning

confidence: 99%

Ranking and Upscaling of Geostatistical Reservoir Models by Use of Streamline Simulation: A Field Case Study

Ates¹,

Bahar²,

Salem

et al. 2005

SPE Reservoir Evaluation &Amp; Engineering

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“…These three realizations were selected from 48 realizations previously generated. 1 The selection was done based on the ranking of Sweep Efficiency (SE), STOIIP and Heterogeneity Index (HI). 7 The sweep efficiency was calculated based on the time-of-flight principle of streamline simulation.…”

Section: Datamentioning

confidence: 99%

“…The approach used in the study was a stochastic approach where multiple reservoir descriptions were generated to quantify the uncertainty in the future performance. 1,2 Reservoir properties for each realization were generated using a geostatistical technique that produces properties, i.e., porosity, permeability and water saturation, consistent with the underlying rock type description. The description was based on core and log data.…”

Section: Introductionmentioning

confidence: 99%

An Innovative Approach To Integrate Fracture, Well Test and Production Data into Reservoir Models

Asnul¹,

Harun²,

Al-Deeb³

et al. 2003

Proceedings of SPE International Improved Oil Recovery Conference in Asia Pacific

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TX 75083-3836 U.S.A., fax 01-972-952-9435. AbstractThis paper presents an innovative approach to integrate fracture, well test and production data into the static description of a reservoir model as an input to the flow simulation. The approach has been successfully implemented into a field study of a giant naturally fractured carbonate reservoir in the Middle East. This study was part of a full field integrated reservoir characterization and flow simulation project.The main input available for this work includes matrix properties, fracture network, well test and production data. Stochastic models of matrix properties were generated using geostatistical methodology based on well logs, core, seismic data and geological interpretation. Fracture network was described in the reservoir as lineaments (fracture swarms) showing two major fracture trends. The network and its properties, i.e., fracture porosity and permeability, were generated by reconciling seismic, well logs, and dynamic data (well test and PLT).The challenge of the study is to integrate all the input in an efficient and practical way to produce a consistent model between static and dynamic data. As a result, it is expected to reduce the history matching effort. This challenge was solved by an innovative iterative procedure between the static and dynamic models.The static part consists of the calibration of model permeability to match the well test permeability. It is done by comparing their flow potentials, kh. In this analysis the dominant factor in controlling production at each well, either matrix or fracture, was determined. Based on the dominant factor, matrix or fracture permeability was modified accordingly. This way the changes in permeability are kept inline with the geological understanding of the field.The dynamic part was carried out through a full field flow simulation to integrate production data. The flow simulation at this stage was used to match production capacity, i.e. to determine whether the given permeability (matrix and fracture) distribution is enough to produce the fluid at the specified pressure during the producing period of the well. The iteration is stopped once a reasonable production capacity match is obtained. In general, a good match was achieved within 3-4 iterations. The generated reservoir description is expected to substantially reduce the effort required to obtain a good history match.

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“…The detailed results of the history match process are beyond the scope of this paper, but can be found in Ref. 1.…”

Section: Figs 5 Andmentioning

confidence: 99%

Reconciling Core Derived Permeabilities and Well Test Using A Fracture Network: A Field Case Example

Mohsen

Maged

Salem

et al. 2002

Proceedings of Abu Dhabi International Petroleum Exhibition and Conference

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractIt is a common observation that well test permeability values do not match with thickness weighted core permeability averages. This is not a surprise because of the differences in the measurement scales where, unlike well test measurements, core samples represent a very small portion of the reservoir around the well bore. In addition, the presence of fractures and/or high permeability channels will further enhance the difference between the two sources of data. Therefore, reservoir descriptions based on core measurements alone cannot honor well test results. They need to be modified properly without violating the underlying geological and geostatistical information.In this paper, we present a methodology to properly enhance permeability fields that also accounts for fracture distribution in the reservoir. The basic idea is that radial upscaling around a wellbore within a given investigation radius should match the permeability obtained from well tests. The enhancement is caused by two factors: microfractures, which cannot be explicitly represented in the reservoir description, and macro-fractures, which can be interpreted using 3-D seismic data. To account for these two different types of fractures, we calculate two different enhancement factors, one for the base level (microfractures) and one for the higher level (macro-fractures). The base level, after appropriate interpolation, is applied across the entire reservoir, whereas the higher level is applied only to locations where macro-fractures are interpreted from 3-D seismic data.The technique was successfully applied to a Middle Eastern carbonate reservoir. A significant correlation is observed between the enhancement required to match the well test data and the fracture density (macro-fractures obtained from 3-D seismic data) within a given investigation area. A correlation function is then obtained between the enhancement factor and the fracture density for a given grid block, which in turn is used to apply enhancement to interwell locations. Thus, the resulting permeability field did not only honor the well test results but also the fracture distribution and the underlying geological and geostatistical descriptions. In a later stage, a tensorial approach was used to upscale permeability to account for the anisotropy in permeability distribution. Using this approach, a proper anisotropy of permeability distribution, matching the fracture orientation, has been obtained.

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Fully Integrated 3D-Reservoir Characterization and Flow Simulation Study: A Field Case Example

Cited by 5 publications

References 11 publications

Ranking and Upscaling of Geostatistical Reservoir Models by Use of Streamline Simulation: A Field Case Study

Ranking and Upscaling of Geostatistical Reservoir Models by Use of Streamline Simulation: A Field Case Study

An Innovative Approach To Integrate Fracture, Well Test and Production Data into Reservoir Models

Reconciling Core Derived Permeabilities and Well Test Using A Fracture Network: A Field Case Example

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