--> ABSTRACT: Gulf of Thailand - Bongkot Field Model-Based 3D Pre-Stack Simultaneous Inversion and Facies Classification, by Manickam, George Soosai; Nyein, Glenn; Berhanu, Solomon Assefa; Goswami, Saumya Kanti; Kwaela, Chaiwat; Bancelin, Jean-Pierre; Sognnes, Helge Ivar; Pooksook, Namfon; Utitsan, Seehapol; Limpornpipat, Orapan; #90155 (2012)

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Gulf of Thailand - Bongkot Field Model-Based 3D Pre-Stack Simultaneous Inversion and Facies Classification

Manickam, George Soosai²; Nyein, Glenn²; Berhanu, Solomon Assefa²; Goswami, Saumya Kanti²; Kwaela, Chaiwat¹; Bancelin, Jean-Pierre¹; Sognnes, Helge Ivar¹; Pooksook, Namfon¹; Utitsan, Seehapol¹; Limpornpipat, Orapan¹
¹Geophysics, PTTEP, Bangkok, Thailand.
²Geophysics, SCHLUMBERGER, Kuala-Lumpur, Malaysia.

Seismic inversion for rock properties plays a major role in the mapping of hydrocarbon bearing reservoirs. In this paper seismic data conditioning for AVO inversion, simultaneous seismic prestack inversion, rock physics analysis and litho facies analysis for lithology and fluid prediction offshore Gulf of Thailand are presented and discussed.

The primary objective of the study was to obtain an improved elastic and lithological characterization of the producing reservoirs, between 1 and 2.5sec (TWT), consisting of Miocene age fluvial deposits, located in shallow marine environment offshore Thailand.

In order to achieve the primary objective, specific seismic data reprocessing and preconditioning has been performed. Residual moveout and gather flatness were addressed through high density velocity analysis and dynamic trim statics, whilst residual multiple energy contamination was addressed through weighted least-squares Radon multiple attenuation.

A Rock Physics model was built using information from six wells located within the study area, and three wells outside the study area. Well log data were analyzed and corrected for mud invasion. Shear velocity was predicted for five wells without shear sonic log.

Seismic to well ties was carried out for six wells. The final wavelet used for inversion was a multi-well least squares wavelet estimation. A Low Frequency Model was generated from the low frequency well trend and constrained by seismic horizons and interval velocities.

The success of this inversion relies mainly in the very accurate QC done at each step of the study, especially during the seismic data reprocessing and preconditioning stages, which enabled producing 5 very reliable angle stacks. Based on the final results a successful blind test performed on a recent development well within the inverted area increases the confidence in the litho-facies prediction away from the calibrated wells.

This new inversion will help refine the lithology and fluid predictions for future exploration wells which may be located more distally from the calibration points used in this study. One of the remaining challenges for a model-based inversion in the fluvial environment of Bongkot is the limited seismic resolution, making it difficult to characterize reservoirs thinner than 4-6m.The possible way forward to improve this technical weakness could be a multi-realization stochastic inversion calibrated on a large number of wells.


AAPG Search and Discovery Article #90155©2012 AAPG International Conference & Exhibition, Singapore, 16-19 September 2012