Ratnaningsih, Dyah Rini and Bintarto, Bambang and Herianto, Topan and Muttaqin, Zaki (2016) The Applied Rock Typing Study: The Link Between Lithofacies Attribute And Pore Geometry-Structure. In: International Conference on Intergrated Petroleum Engineering & Geosciences (ICIPEG 2016), 15 - 17 August 2016, Kuala Lumpur Convention Centre.
|
Text
The Applied Rock Typing Study The Link Between Lithofacies Attribute And Pore Geometry-Structure.pdf Download (12MB) | Preview |
Abstract
Well ‘A’ was done conventional coring (6787-6963 MD) at sandstone reservoir ‘X’. Core analysis results 126 core samples for RCAL and core description, 6 core samples for SCAL, petrography (XRD and photomicrographs). As see this core availability, the reservoir ‘X’ needs to have reliable and quick reservoir characterization, we have appeared idea to conduct rock type using Pore Geometry Structure (PGS). Because of most cases, petrophysical data has been used traditionally for purpose of predicting permeability based on permeability-porosity semilog plot without understanding its spread. Permeability is one of the most important parameter, it should have been predicted if the selection of rock typing itself is correct. This study are to characterize rock type of reservoir,to predict permeability and to get initial production test close to actual test. Classifying rock type is initiated by considering the lithofacies attribute (lithology, color, rock texture and mineralogy composition). They are then plotted into PGS plot, X-axis is (k/ø^3) as pore structure, Y-axis is (v(k/ø)) as pore geometry. Each rock type will have distinct line whose slopes no more than 0.5. Once established, rock type equation is merged with initial-saturation = f(permeability) equation, then porosity-saturationpermeability correlations are formed to result equation predicting permeability that is valid to core data. Continued by applying rock region into single well radial model based on kCore and k-PGS, respectively. The results are PGS plot has shown 9 rock types based on lithofacies attribute; permeability prediction equation has been valid through core data (R = 0.9951). Hence, it could be used for predicting permeability on the wells that do not have core data at reservoir. The initial production test simulation shows PGS-model has approached actual initial production test. This could be an alternative reservoir characterization using reliable core data which leads to a well-built reservoir model.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
| Depositing User: | Ir.Drs Herianto Topan |
| Date Deposited: | 23 Apr 2019 04:58 |
| Last Modified: | 23 Apr 2019 06:40 |
| URI: | http://eprints.upnyk.ac.id/id/eprint/9743 |
Actions (login required)
 |
View Item |