AI SearchApplication of ANN analysis in prediction of reservoir porosity for an oil field in the Northern Pattani Basin (Record no. 6472)
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| fixed length control field | 05759nas a2200469 a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260817162833.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 121109s2011 th r 000 eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12114698 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.OTM-11-05 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Nicha Nakapraves |
| 245 10 - TITLE STATEMENT | |
| Title | Application of ANN analysis in prediction of reservoir porosity for an oil field in the Northern Pattani Basin |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2011 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 180 p. : |
| Other physical details | ill. (some col.) |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. OTM-11-05 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Offshore Technology and Management, School of Engineering and Technology |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M. Eng) - Asian Institute of Technology, 2011 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | The study area is located in North Pattani Basin, Gulf of Thailand. Although the major wells in the interested area did have logging and coring, not all depth intervals could be cored and not all logging curves were measured. Some logs were even missing. Assessment or prediction of petrophysical parameters, including porosity in uncored intervals and at other wells locations may have an impo1tant role in the reserve estimation. To help so lving this issue, Back-propagation Artificial Neural Network (ANN) with early stopping method was employed in this study to help estimate porosity from well logging data or seismic attributes. Well logging data and core measurement of two wells (wells A and B) were studied. Quicklook interpretation was conducted in order to identify reservoir, estimate shale volume, porosity, permeability, and water saturation. The Back-propagation ANN with early stopping method was studied and applied for porosity prediction by using Matlab software. The data sets were separated into three subsets, i.e. training, validating, and testing. The input data were from well logging data or seismic attribute data. The output data used for training were from core porosity. The ANN model with least performance error was applied for porosity prediction in uncored well and other wells locations. The first group of ANN analyses used the well logging data as input layer with the standard set consisting of GR, LLD, RHOB, NPHI, and DT. The desired output data were core porosity measurements. The tangent hyperbolic function was employed as transfer function for the hidden layer, while the linear function was used as transfer function for the output layer. A total of 56 ANN analyses were performed to predict porosity for uncored intervals. It was found that the ANN-based porosity of the best model matched very well with core porosity, MSE was 10.09. Within this first group of ANN analyses, it is wo1th mentioning that a number of analyses were done for the case the sonic log (DT) was missing. To solve this problem of missing DT, the synthetic DT curves were reconstructed using both methods of Log Response Equation (LRE) and ANN. As a good finding of this study, the DT curves were well reconstructed, MSE was 80.41. Again, based on the reconstructed DT, a complete input data layer including GR, LLD, RHOB, NPHI, and DT, was obtained for the ANN analysis, MSE was 9.22. The second group of ANN analyse was conducted with the major change in the input layer, with the input data being se ismic attributes (dip, azimuth, instantaneous phase, and relative acoustic impedance). These seismic attributes were extracted from seismic cube by Petrel software. A total of 6 ANN analyses were run to study the seismic attribute sensitivity. The matching of ANN-based porosity was not that good as those obtained in the first group. The best results obtained were obtained for the case using all seismic attributes as input data, MSE was 44.30. However, the result was encouraging in the sense that if seismic attributes could be successfully used as the input data in an ANN analysis one has good opportunity to make a satisfactory 3D petrophysical modelling (or 3D distribution of porosity in this case) for the concerned oil field. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Oil fields |
| Geographic subdivision | Pattani Basin |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Pham, Huy Giao, |
| Relator term | Chairperson |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chiu, Gregory L.F., |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Noppadol Phien-Wej, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Royal Thai Government Fellowship, |
| Relator term | Scholarship donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Thesis ; |
| Volume/sequential designation | no. OTM-11-05 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B11282">http://203.159.5.9/ait-thesis/detail.php?q=B11282</a> |
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| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 130215 |
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| Koha item type | 20-AIT Publication |
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| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Cost, normal purchase price | Total checkouts | Full call number | Barcode | Date last seen | Copy number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 17/08/2026 | 50.00 | AIT Thesis no.OTM-11-05 | 30050120685440 | 17/08/2026 | 1 | 17/08/2026 | 20-AIT Publication | ||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 17/08/2026 | 50.00 | AIT Thesis no.OTM-11-05 | 30050120387583 | 17/08/2026 | 2 | 17/08/2026 | 20-AIT Publication | ||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no.OTM-11-05 | 30050160006101 | 17/08/2026 | 1 | 17/08/2026 | 40-Archives | |||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | 50.00 | AIT Thesis no.OTM-11-05 | 30050211014328 | 17/08/2026 | 3 | 17/08/2026 | 20-AIT Publication | ||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | 50.00 | AIT Thesis no.OTM-11-05 | 30050211014310 | 17/08/2026 | 4 | 17/08/2026 | 20-AIT Publication |