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THE STUDY OF RESERVOIR DISTRIBUTION AND CONNECTIVITY USING SEISMIC ATTRIBUTES, CENTRAL PATTANI BASIN, GULF OF THAILAND |
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| รหัสดีโอไอ | |
| Creator | Nusara Adisaipattanakul |
| Title | THE STUDY OF RESERVOIR DISTRIBUTION AND CONNECTIVITY USING SEISMIC ATTRIBUTES, CENTRAL PATTANI BASIN, GULF OF THAILAND |
| Contributor | - |
| Publisher | Department of Geology, Chulalongkorn University |
| Publication Year | 2560 |
| Journal Title | Bulletin of Earth Sciences of Thailand (BEST) |
| Journal Vol. | 9 |
| Journal No. | 2 |
| Page no. | 53-61 |
| Keyword | Reservoir distribution, Reservoir connectivity, Reservoir compartments, Seismic attributes, Variance attribute, RMS amplitude |
| URL Website | https://www.bestjournal.org/ |
| Website title | Bulletin of Earth Sciences of Thailand |
| ISSN | 1906-280X |
| Abstract | Reservoir distribution and connectivity in the Pattani Basin, Gulf of Thailand is always a challenging issue. The reservoirs are relatively thin fluvio-deltaic sands (7-70 ft (2-20 m) on average) and highly compartmentalized by rapid lateral and vertical stratigraphic changes, as well as having an abundance of faults. In order to maximize the production economics, the reservoir connectivity which plays a major role in how the reservoirs are managed and developed must be well understood. This study is aimed to gain a better understanding on reservoir connectivity at 3 sand levels, 3650 ft (1.11 km) (Sand1), 4500 ft (1.37 km) (Sand2) and 7000 ft (2.13 km) (Sand3) true vertical depth sub-sea level (TVDSS). The main 4 possible causes that might result in the not-connected reservoirs among wells are 1) mis-correlated sands, 2) faulted sands 3) internal compartmentalized sands and 4) separated sands. Many seismic attributes were tested to improve fault images. The results of the best fault implication attribute (Variance attribute) showed that there is no major fault amongst well distribution at all 3 sand levels. The sand connectivity study then integrated the Root Mean Square (RMS) amplitude maps that are sand-predictive maps to the well log correlation, pressure data and production-injection data. It revealed that the RMS amplitude can help determine the spatial reservoir distribution, this leads to the more visual reservoir connectivity prediction further to wells without pressure data and/or being perforated. The recommendations for the future sand perforation at Sand1 level and the proposed injector well at Sand3 level have been made to recover the un-swept reserves. |
