التفاصيل البيبلوغرافية
| العنوان: |
Production data-based facies analysis for well placement in thin-layered reservoir |
| المؤلفون: |
Xuequn Tan, Shiwang Chen, Taiyuan Hong, Yuliang Feng, Qiang Ding |
| المصدر: |
Energy Geoscience, Vol 3, Iss 3, Pp 219-234 (2022) |
| بيانات النشر: |
KeAi Communications Co., Ltd., 2022. |
| سنة النشر: |
2022 |
| المجموعة: |
LCC:Production of electric energy or power. Powerplants. Central stations |
| مصطلحات موضوعية: |
Tide-dominated estuary, Well-log facies, Sand-body connectivity, Well performance, Oriente Basin, Production of electric energy or power. Powerplants. Central stations, TK1001-1841 |
| الوصف: |
The exploitation of a thin-layered reservoir with thickness less than 5 m (16 ft) needs to rely upon sedimentary facies analysis, due to the low resolution of seismic data and sparse well data. However, the ambiguity of facies interpretation creates uncertainty in facies and reservoir mapping. The study aims to better define facies distribution, predict sand-body architecture, and consequently reduce risks in planning development wells, by integrating production data (dynamic) with conceptual geological models (static). An example is shown from the M1 Member of the Napo Formation in the B and G Oilfields (Block J), Oriente Basin, Ecuador. The M1 reservoir is a thin-layered sandstone reservoir below seismic resolution. Core and well-log facies interpretation indicates depositional facies of a tide-dominated estuary. Production data during the water injection phase of field development can delineate the detailed geometry of the sand bodies. The injector-producer rate responses can determine the connectivity of sand bodies. Well performance during primary recovery can capture the scale of single reservoirs because the initial production rates and the cumulative oil production of individual wells are generally proportional to the size of sand bodies. A facies model was thereby generated. Two step-out wells were planned using this model and drilled successfully. The results demonstrate that the integration of dynamic and static data is critical to understanding reservoir facies distribution. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2666-7592 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2666759222000208; https://doaj.org/toc/2666-7592 |
| DOI: |
10.1016/j.engeos.2022.03.002 |
| URL الوصول: |
https://doaj.org/article/bd5d069a49844d0799ef0a492e2849ea |
| رقم الانضمام: |
edsdoj.bd5d069a49844d0799ef0a492e2849ea |
| قاعدة البيانات: |
Directory of Open Access Journals |
Full Text Finder