A Fully Integrated Approach for Better Determination of Fracture Parameters Using Streamline Simulation; A gas condensate reservoir case study in Iran

Document Type: paper

Authors

Research Institute of Petroleum Industry, Tehran, Iran

Abstract

 Many large oil and gas fields in the most productive world regions happen to be fractured. The exploration and development of these reservoirs is a true challenge for many operators. These difficulties are due to uncertainties in geological fracture properties such as aperture, length, connectivity and intensity distribution. To successfully address these challenges, it is paramount to improve the approach of characterization and simulation of fractured reservoirs.
In this study, a fully integration of all available data and methods have been used for generating stochastic discrete fracture network (DFN)such as outcrop study, core description, petrophysical and image logs and also for better result validation, streamline simulation has been conducted. In this comprehensive process a real gas condensate fractured carbonate reservoir has been used.
Firstly, three main fracture sets were defined that have fold-related fractures, then the fracture intensity and DFN model using fracture drivers correlation were generated. After that, permeability of the developed DFNs was calibrated with available well test permeability. Then, a streamline simulation was used because of its high computational speed, high accuracy and good visualization for the repeated nature of history matching of a dual porosity model in the gas condensate reservoir. So, with running streamline simulation, three realizations (High, Medium and Low) ranked based on the objective function values. These three realizations are common realization that are well known with optimistic, most likely and pessimistic scenarios. Finally, comprehensive history matching was done for all the three-selected realizations.
The overall goal is to develop a representative fluid flow simulation model for improving gas cycling procedure in gas condensate reservoir. This method has great application in the high resolution fractured reservoir modeling due to using actual fracture parameters. Also, it can be used for model ranking, screening and optimum dynamic model calibration for reduction of the history matching complexity without being manipulated by reservoir engineer.     

Keywords


[1] Aguilera, R. (2003). Geologic and Engineering Aspects of Naturally Fractured Reservoirs. Canadian Society of Exploration Geophysics Recorder (February), pp. 44-49.

[2]  Acuna,  J.A.,  Ershaghi,  I.  and  Yortsos,  Y.C.  (1995).  “Practical  application  of  fractal pressure-transient analysis in naturally fractured reservoirs.” SPEFE 173; Trans.,  AIME,299.

 [3] Christie, M., Subbey. S., Sambridge, M. and Thiele, M. (2002). Quantifying  Prediction Uncertainty in Reservoir Modeling Using Streamline Simulation. 15th  ASCE Engineering Mechanics Conference June 2-5, 2002, Columbia University, New York, NY.

[4] Datta-Gupta, A. (2000). Streamline Simulation: A Technology Update. JPT 68.

[5] Di Donato, G., Huang, W. and Blunt, M.J. “Streamline-based dual porosity simulation of fractured reservoirs." Paper SPE 84036 presented at the  Annual Technical Conference and Exhibition, Denver, CO, 5-8 October.

[6] Dershowitz, W., et al. (2003). “Integration of discrete fracture network methods  with conventional simulator approaches,” SPE Res. Eval. & Eng., pp. 165-170, (April 2000).

[7] Guerreiro, L. et al. (2000). “Integrated reservoir characterization of a fractured carbonate reservoir.” SPE 58995, SPE Inter. Petroleum Conf. and Exhib., Villahermosa, Mexico.

[8] Gilman, J.R. et al. (2002). “Statistical ranking of stochastic geomodels using  streamline simulation: A field application.” paper SPE 77374 presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 29 September–2 October.

[9] Idrobo, E. A. (1999): “Characterization and ranking of reservoir models using geostatistics and streamline simulation.” PhD Dissertation, Texas A&M University.

[10]  Haldorsen,  H.H.  and  Damsleth,  E.  (1993),  Challenges  in  reservoir  characterization.AAPG Bulletin, 77(4), pp. 541-551.

[11]  Kazemi,  H.,  Atan,  S.,  Al-Matrook,  M.,  Dreier  J.  and  Ozkan,  E. (2005).  Multilevel Fracture Network Modeling of naturally fractured Reservoirs. SPE 77741 presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas U.S.A, Jan. 31-Feb. 2.

[12] King, M. J. and Datta-Gupta, A. (1998). "Streamline simulation: A current perspective." In Situ,22(1): pp. 91-140.

[13] Guttormsen, Li, B., Tran, J. and Hoi, V. (2004). Characterizing Permeability for  the Fractured  Basement  Reservoirs.  SPE  88478 presented  at  the  SPE  Annual  Technical Conference and Exhibition, Perth, Australia, 18–20 October.

[14] Milliken,  W.  J.,  Emanuel,  A.  S.  and  Chakravarty,  A.  (2001). Applications  of  3D Streamline Simulationto Assist History Matching. SPE 74712, SPE Reservoir Evaluation & Engineering, 4 (6), December, 502-507.

[15] Nelson,  R.  A.  (1985).  Geological  Analysis  of  Naturally  Fractured Reservoirs,  GulfPublishing Company, Houston.

[16] Reynolds, A. C., He, N. and Oliver, D.S. (1997). “Reducing uncertainty in geostatistical description   with   well   testing   pressure   data.”   in  Proc.,    International    Reservoir Characterization Conference, Houston, 2-4 March.

[17] Baker, R.O., Kuppe, F., Chugh, S., Bora, R., Stojanovic, S. and Batycky, R. (2002). “Full- field modeling using streamline-based simulation: Four case studies.” SPE Reservoir Eval.& Eng., 5 (2).

[18] Tamagawa,  T.,  Matsuura,  T.,  Anraku,  T.,  Tezuka,  K.  and Namikawa,  T.  (2002), “Construction of fracture network  model using static and  dynamic data.” SPE  77741 presented at the SPE Annual Technical Conference and Exhibition, San Antonio, TX, Sept 29-Oct. 2.

[19] Verga, F.M., Giglio, G., Politecnico  di Torino, Masserano, F. and  Ruvo, L. (2002). Validation  of  Near-Wellbore  Fracture-Network Models  with  MDT.  April  2002  SPE Reservoir Evaluation & Engineering.

[20] Wang,  Y.  and  Kovscek,  A.R.  (2000).  “Streamline  approach  for history  matching production data.” SPE  Journal, (4), pp. 353-362.

[21] Zubiri, M. and Silvestro, J. (2007). "Fracture modeling in a dual porosity volcaniclastic reservoir: A case study of the precuyo group in cupen mahuida field, Neuquén, Argentina. AAPG Annual Convention, Long Beach, California, April 1-4.