Rock Type Constrained 3D Reservoir Characterization and Modeling

Silva, Fernando; Ghani, Ahmed; Mansoori, Abdulla; Asnul, Bahar

doi:10.2523/78504-ms

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…The use of geostatistics in permeability prediction provides an additional uncertainty group that may be added into the hierarchical system of the multiple realizations scheme. 5 An important feature that needs to be satisfied for each realization is that the petrophysical properties have to be consistent with the underlying geological description of the field. That is, the generated properties, namely porosity and permeability, should be in agreement with the underlying facies/rock type description.…”

Section: Approach Implementation and Resultsmentioning

confidence: 99%

Practical Approach in Modeling Naturally Fractured Reservoir: A Field Case Study

Bahar¹,

Ates²,

Al-Deeb

et al. 2003

SPE Annual Technical Conference and Exhibition

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper presents a practical approach in modeling a naturally fractured reservoir. The approach was used for a field study of a giant carbonate reservoir in the Middle East. The method is shown to be practical and comprehensive and yet has produced good results. It consists of a fully integrated effort from geological, geophysical and engineering disciplines. The overall goal of the study is to develop a representative reservoir model to form the basis for reservoir management and long-term development planning.The approach consists of the following procedures:• Generation of multiple realizations of matrix property using geostatistical techniques. The standard cosimulation procedure was implemented to ensure the consistency among reservoir properties, namely rock type, porosity and permeability. • Generation of multiple realizations of 3D fracture property by reconciling seismic, well logs and dynamic data. These were obtained from curvature analysis and seismic facies map validated by borehole image and dynamic data. The fracture network was described in the reservoir as lineaments (fracture swarms) showing two major fracture trends. • Calibration of the model permeability with well testderived permeability considering fracture distribution. A newly developed technique was implemented to ensure that the fine scale model (i.e., geological model) honors well test as well as production data before it was subjected to the flow simulation. The technique also generates permeability anisotropy to account for fracture orientations.• Ranking of multiple realizations using streamline simulation to select three representative realizations (low, medium and high models).• Upscaling of reservoir properties, including vertical upscaling level optimization using streamline simulation. • History matching and future performance prediction of the three selected realizations as a single media model. The use of single media model was based on the observation of relatively high matrix permeability in the major producing zone. However, for comparison purposes, a dual media model was also developed.• Uncertainty analysis of the future dynamic performance using a probabilistic approach. The procedure described above has been implemented successfully in a field study. The use of a calibration process in the geological model reduces the number of parameters that need to be adjusted during history matching. Consequently, history matching may concentrate on the uncertainty in parameters that have not been specifically accounted for in the geological modeling stage, such as relative permeability and aquifer size/strength.

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Section: Approach Implementation and Resultsmentioning

confidence: 99%

Practical Approach in Modeling Naturally Fractured Reservoir: A Field Case Study

Bahar¹,

Ates²,

Al-Deeb

et al. 2003

SPE Annual Technical Conference and Exhibition

View full text Add to dashboard Cite

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Seismic Integration for Better Modeling of Rock Type Based Reservoir Characterization: A Field Case Example

Bahar¹,

Abdel-Aal

Ghani

et al. 2004

Abu Dhabi International Conference and Exhibition

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This paper presents the result of a reservoir study where seismic data have been fully utilized to obtain a better rock-type based reservoir characterization model. The study was conducted for a highly faulted carbonate reservoir in the Middle East. The available 3D Seismic data have been used to determine the structure map, fault and fracture network, and porosity distribution. Additionally, two seismic attributes (Energy Half Time and Max. Peak Amplitude) had also been used to assist the determination of stationarity regions used for geostatistical simulation. The reservoir characterization strategy for this study was started with the detailed development of a geological reservoir rock type (RRT) scheme. The RRT scheme was developed based on depositional facies, diagenetic overprints and petrophysical properties, including pore throat size distribution, porosity and permeability. The scheme was then used to constrain the property modeling inside a geological framework that was built based on the seismic interpretation. Prior to the development of 3D porosity model, four porosity maps were generated based on the available interpreted Acoustic Impedance (AI) and well log data. Each map represents the difference of the influence of seismic data, from full seismic influence to no seismic influence. One map has been selected to represent the seismic derived porosity based on the degree of correlation between the AI data and well-log porosity. The integration of seismic-derived porosity into the 3D simulation model was conducted using Bayessian Update principle inside a conditional simulation technique. In this technique, 3D porosity distribution honors the underlying RRT and at the same time its vertical-column average honors seismic-derived porosity. The comparison of the results between the simulation with seismic and simulation without seismic has clearly indicated the value added by seismic data, namely improving the simulation result in the areas of poor well-coverage. This is important in order to honor the diagenesis effect that is difficult to model due to a limited number of wells. Introduction Simplified models for describing reservoirs with complex geology are not able to adequately represent the reservoir heterogeneities and their impact on connectivity patterns and flow mechanisms. A critical step in the construction of reservoir simulation models is the description of the underlying reservoir geology. This is even more mandatory in the case of carbonate reservoirs, frequently characterized by an intensive diagenetic overprint of the original carbonates. This process frequently includes assessing the complex reservoir internal architecture reflected in the internal discontinuities within the lithological units, vertical and lateral variation of rock properties and similar heterogeneities within the reservoir layers. The state of the art technology in generating reservoir models is to start with proper characterization of the underlying geology. The result of the characterization should be used in generating the 3-D model. The challenge that needs to be considered from the start is how the model can replicate the reality, i.e., what is defined during the characterization process. To cope with the geological complexity and assist in understanding the property distribution in highly heterogeneous reservoirs, the concept of "Rock Types" was introduced and has been widely used as a basis for reservoir characterization in recent years. Typically, once reservoir rock type was determined and distributed in the 3D volume, the next task is to generate properties, namely porosity, permeability, and saturation, based on the well data (log and core). Ideally, these properties should be generated in such away that they are consistent among each other. Depending on the availability of the data, additional data integration may be done to improve the property model. The objective of this study is to provide a consistent property model by integrating geological based rock type, well log/core and seismic data. In this objective, seismic data is used to further improve porosity model, which was originally constrained to rock type and well log data only.

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Rock Type Constrained 3D Reservoir Characterization and Modeling

Cited by 2 publications

References 4 publications

Practical Approach in Modeling Naturally Fractured Reservoir: A Field Case Study

Practical Approach in Modeling Naturally Fractured Reservoir: A Field Case Study

Seismic Integration for Better Modeling of Rock Type Based Reservoir Characterization: A Field Case Example

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