There are a lot of uncertainties associated with building geostatistical models which are important to take into account. The model is mainly a result of the input parameters given by the seismic data. The limitation of the amount and quality of the available data makes it impossible to build a geological model with 100% confidence. It is impossible to exactly describe the existing state in the subsurface and there is more than one possible outcome of the model. The risk is that some of the possible outcomes or simplifications have undesired effects or significant loss of information.
In this study the input parameters for the deterministic model were previous interpreted channels and channel belt facies derived from high resolution seismic data (Samorn, 2006).
CHAPTER SEVEN - CONCLUSIONS
In this study a series of seismic time-slices have been used to identify the fluvial architecture of the Pattani Basin in the Gulf of Thailand. This high resolution dataset has been exploited to build a deterministic reservoir model (Fig. 3.10) which has been further used to compare the results of a variety of object-based and MPS modelling strategies.
The deterministic model provides a basis for analysing the depositional system. Overall there is an increase in the proportion of channel belt facies downwards which is associated with an increase in the connectivity and a decrease in the number of isolated sandbodies. There is no associated change in channel belt or channel geometries suggesting preservation over
overbank controlled by subsidence rate was the key control on net:gross rather than a change in fluvial style. There is an absence of clear point bars in the lower part of the interval which may be related to either a change in fluvial style (to more braided) or a loss of seismic resolution.
When comparing the models visually the object-based models contained the right facies proportions, but the modelled objects looked too smooth and unrealistic. The modelling process was also more time consuming than the MPS modelling since only one facies could be modelled at a time and each object had to be described thoroughly before the facies could be combined. The MPS models did not match the facies proportions as well as the object- based models, but the bodies showed more flexibility in geometry and looked more realistic than the object-based models. The problem with ergodicity still has to be addressed.
Connectivity was used to assess the effectiveness of the different modelling strategies. The results from the connectivity analyses indicate that modelling point bar facies might be unnecessary when looking at reservoir fluvial connections. The connectivity proved better in the deterministic model than in the object-based model, also indicating that modellers may under-estimate reservoir connectivity when looking at large scale fluvial systems. The
connectivity analysis of the MPS model resulted in one large volume and several minor ones. The MPS model over-estimate the connectivity compared to the deterministic model. The reason could be that the training images the 3D model is made of were too similar.
The comparative study suggests that the MPS method better produced the character of the system but still had limitations. The computational effort when using large training images is currently too high and the models suffered from small not stationary images which failed to reproduce the continuity of the bodies. The program has difficulties in reproducing continuous large-scale structures like the meandering channels that runs through the entire model;
therefore better training images are required. Establishing a catalogue of training images together with a training image builder for complex 3D reservoirs would also make the modelling process more practical and user friendly.
Incorporating more geological data into reservoir modelling ensures that the final numerical model is more geological robust, which is essential for prediction of flow in reservoirs. By looking at 3D reservoir models of fluvial systems it is possible to study the lateral migration of channels and channel belt facies together with vertical aggradational patterns.
The next, natural step working with this data would be to compare the deterministic model with large outcrop analogues. When comparing the heterogeneity one might be able to increase the general understanding of fluid flow patterns in the subsurface.
Boggs, S., 2006, Principles of sedimentology and stratigraphy, Pearson Prentice Hall.
Caers, J., 2001, Geostatistical reservoir modelling using statistical pattern recognition: Journal of Petroleum Science and Engineering v. 29, p. 177-188.
Caers, J., and Zhang, T., 2002, Multiple-point geostatistics: a quantitative vehicle for integrating geologic analogs into multiple reservoir models: Computers & Geosciences, v. 30, p. 741-751.
.
Clemetsen, R., Hurst, A.R., Knarud, R., and Omre, K.H., 1990, A computer program for evaluation of fluvial reservoirs, in Buller, A.T., Berg, E., Hjelmeland, O., Kleppe, J., Torsaeter, O., and Aasen, J.O., eds., North Sea oil and gas reservoirs II: London, Graham and Trotham.
Deutsch, C.V., and Tran, T.T., 2002, FLUVSIM: A program for object-based stochastic modeling of fluvial depositional systems: Computers and Geosciences, v. 28, p. 525- 535.
Holden, L., Hauge, R., Skare, O., and Skorstad, A., 1998, Modeling of fluvial reservoirs with object models: Mathematical Geology, v. 30, p. 473-496.
Howell, J.A., and Flint, S.S., 2005, Sequence stratigraphical evolution of the Book Cliffs succession, in Coe, A.L., ed., The sedimentary record of sea-level change: Cambridge, The Open University, Cambridge University Press, p. 198-208.
Jardine, E., 1997, Dual petroleum systems governing the prolific Patani Basin, offshore Thailand, Petroleum Systems of SE Asia and Australasia Conference: Jakarta, Indonesian Petroleum Association.
Geol, v. 76, p. 1601-1624.
Kearey, P., Brooks, M., and Hill, I., 2002, An Introduction to Geophysical Exploration, Blackwell Publishing.
Keogh, K.J., Martinius, A.W., and Osland, R., 2007, The development of fluvial stochastic modelling in the Norwegian oil industry: A historical review, subsurface
implementation and future directions, Sedimentary Geology, v. 202, p. 249-268.
Knai, T.A., and Knipe, R.J., 1998, The impact of faults on fluid flow in the Heidrun Field, in Jones, G., Fisher, Q.J., and Knipe, R.J., eds., Geological Society Special Publication, Volume 147, p. 269-282.
Knudsen, T., 2008, Application of 3D, geocellular modelling to understand the large scale stratigraphic architecture and stacking patterns in the Cretaceous Central Utah, USA: Bergen, University of Bergen.
Kornsawan, A., and Morley, C.K., 2002, The origin and evolution of complex transfer zones (graben shifts) in conjugate fault systems around the Funan field, Pattani Basin, Gulf of Thailand: Journal of Structural Geology, v. 24, p. 435-449.
Liu, Y., Harding, A., Abriel, W., and Strebelle, S., 2004, Multiple-point simulation integrating wells, three-dimensional seismic data, and geology: AAPG Bulletin, v. 88, p. 905-921.
MacDonald, A.C., and Aasen, J.O., 1994, A prototype procedure for stochastic modeling of facies tract distribution in shoreface reservoirs, in Yarus, J.M., and Chambers, R.L., eds., AAPG Computer Applications in Geology, Volume 3, p. 91-108.
Manzocchi, T., Walsh, J.J., Nell, P., and Yielding, G., 1999, Fault transmissibility multipliers for flow simulation models: Petroleum Geoscience, v. 5, p. 53-63.
1216.
Morley, C.K., 2001, Combined escape tectonics and subduction rollback-back arc extension: a model for the evolution of Tertiary rift basins in Thailand, Malaysia and Lagos: Journal of the Geological Society, London, v. 158, p. 461-474.
Morley, C.K., and Westaway, R., 2006, Subsidence in the super-deep Pattani and Malay basins of Southeast Asia: a coupled model incorporating lower-crustal flow in response to post-rift sediment loading: Basin Research, v. 18, p. 51-84.
O'Brien, P.J., 2001, Subduction followed by collision: Alpine and Himalayan examples: Physics of the Earth and Planetary Interiors, v. 127, p. 277-291.
Posamentier, H.W., 2001, Lowstand alluvial bypass systems: Incised vs unincised: AAPG Bulletin, v. 85, p. 1771-1793.
Samorn, H., 2006, Fluvial reservoir architecture from near-surface 3D seismic data, Block B8/32, Gulf of Thailand. Unpublished M.S. thesis, Colorado School of Mines.
Schumm, S.A., 1994, Erroneous perceptions of fluvial hazards: Geomorphology, v. 10, p. 129-138.
Stanley, K.O., Jorde, K., Raestad, N., and Stockbridge, C.P., 1990, I. Stochastic modeling of reservoir sand bodies for input to reservoir simulation, Snorre Field, northern North Sea, Norway, North Sea oil and gas reservoirs; II. Proceedings of the North Sea oil and gas reservoirs Conference, p. 91.
Watcharanantakul, R., and Morley, C.K., 2000, Syn-rift and post-rift modelling of the Pattani Basin, Thailand: evidence for a ramp-flat detachment: Marine and Petroleum Geology, v. 17, p. 937-958.