ABSTRACT
APPLICATIONS OF DATA ANALYSIS PRINCIPLES FOR THE PREDICTION OF RESERVOIR QUALITY OF THE ELMA FIELD NIGER DELTA
Journal: Big Data In Water Resources Engineering (BDWRE)
Author: Onome O. Okobiebi, Delik Celik, Kenneth Ojeaga
This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
DOI: 10.26480/bdwre.01.2025.01.06
This study investigates the application of data analysis on well-log data to ascertain the distribution of potential reservoir sands in the ELMA field Niger Delta. The data used for the analysis consists of the 14 wells that penetrated the ELMA field. The field consists of various lithologies interpreted from the core ranging from channel sands (CH), Lower Shore face (LSF), Upper Shore face (USF), Heterolith (HT) and Shales (SH).These Well data were cleaned and plotted using Python script and analyzed using charts and tables to as certain the percentage distribution of each facies in the field and the overall percentage of viable pay sands in the field. The analysis showed that the distribution of lithologies was 52.74% for SH, 22.69 for USF, 20.70for CH, 2.75 for LSF and 1.11 HT. The overall net pay of the field was 47.3% which points to a high reservoir potential in the field with an accompanying possibility of sealing shale of 52.7%.
| Pages | 01-06 |
| Year | 2025 |
| Issue | 1 |
| Volume | 6 |
