Time-lapse geochemical exploration utilizing a multi-depth sampling design

• Published in: IOP conference series. Earth and environmental science Vol. 360; no. 1; pp. 12001 - 12007
• Main Author: AbuAli, Mahdi
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.10.2019
• Subjects: Air sampling; Anomalies; Calibration; Depth profiling; Drilling; Dry wells; Exploratory drilling; Geochemistry; Hydrocarbons; Neural networks; Oil exploration; Optimization; Petroleum; Petroleum hydrocarbons; Reservoirs; Sampling; Sampling designs; Seepage; Sensors
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/360/1/012001

The objective of this proposed surface geochemical exploration method is to design a sampling survey in a different way than has been done conventionally. Traditionally, surface sampling is carried out at a depth ranging from 0.5-1.0 meters. A new patented method is proposed to test different depth intervals to reach the optimum depth. The survey is then repeated to verify whether the same results are consistently obtained (time-lapse). A regional east-west transect was chosen to test whether the multi-depth approach would reveal a depth-seepage relationship. The area of interest is ideal for such a study because of its relatively simple petroleum system setting. Hydrocarbons are derived from a single source and trapped in a single reservoir, thereby minimizing or eliminating the risk of confusing signals from multiple reservoirs. The transect runs through a producing well and a dry well for calibration purposes. The geochemical sensors were placed at 1, 5 and 10 meter depths using drilled cased holes along the transect. The sensors were collected after three weeks. A regional trend was established and a comparative model was created, which allowed for contrasting the different depth profiles and validating the resultant geochemical signatures with the typical signature in the area. Encouraging results were achieved from multi-depth seepage profiling in the field, but they were limited by the relatively sparse transect sample pattern. Distinct conclusions were apparent when using both light and mid-range compounds (C2-C5 and C6-C10). The geochemical anomalies suggested an optimal sampling depth for seepage detection based on this study. In some instances positive anomalies were present over undrilled leads in the area. The dataset was modelled using both neural network and linear discriminant techniques. More follow-up work is underway to validate the results by varying the depth profiles, using cased holes vs. non-cased holes, sampling air blanks and repeating the survey to confirm reproducibility of the results (time-lapse effects). The results from this study require validation and future development to improve the technology of multi-depth geochemical profiling before these techniques can be made routine in hydrocarbon exploration. The survey can be conducted concurrently with seismic acquisition to prove the presence of a petroleum charge before making more expensive decisions whether in seismic acquisition or in exploration drilling.