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A Quick-look Reservoir Characterization and Electrofacies Workflow Provides New Insight into the Early Miocene Reservoirs of the Chim Sao Field, Nam Con Basin, Vietnam

Carney, Steve; Dun, Dinh Tran; Thanh, Nguyen; Nieuwland, Ferry; Taylor, David; Bulgauda, Suryakant
Premier Oil, Ho Chi Minh City, Viet Nam.

The Chim Sao Oil and Gas Field is located in Block 12W in the Nam Con Basin offshore Vietnam. Production comes from Early Miocene Middle Dua stacked heterogeneous clastics, deposited in a tide modified deltaic/estuarine setting. There are challenges in developing these reservoirs associated with a complex depositional setting, internal architectural complexity, fine scale heterogeneity and complex mineralogy. A combination of a holistic data integration approach and the application of quick-look reservoir characterisation and electrofacies techniques resulted in an enhanced understanding of reservoir distribution and properties which underpins the successful development of this important field.

A holistic data integration approach involving the integration of geological, petrophysical, geophysical and reservoir engineering data in one software platform facilitated interrogation of cross-disciplinary data. A key component of the study involved the application of some simple quick-look empirical and data charactersiation techniques based on porosity and permeability log data. These include Winland (R35) pore throat analysis, Rock Quality Index (RQI), Reservoir Flow Capacity (Kh) and Storage Capacity (Phieh). Stratigraphic and Modified Lorenz plots were also generated to determine flow capacity and storage capacities in key reservoirs calibrated to dynamic data. These approaches helped rank reservoirs based on quality and an improved understanding of vertical and lateral reservoir continuity.

A multi-resolution graphical clustering (MRGC) electrofacies approach was used to characterize reservoirs using Vshale, effective porosity and total porosity input logs. The MRGC, coarse to fine self organizing maps approach is a non-parametric graphical method which partitions data sets on the basis of their "data structure". Based on neighboring relationships, data points are progressively clustered into electrofacies. This is an elegant, impartial and reproducible approach which has wide applications.

Key lessons learnt include, the importance of acquiring good, representative data and benefits of a centralized data repository which facilitates data interrogation and integration. Success was achieved on a highly complex problem through the application of an integrated, multidisciplinary work flow and new technology. This approach is quick, cost effective and has wide applications in other complex fields.


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