TY - JOUR
T1 - Direct interpretation of petroleum reservoirs using electromagnetic radiation anomalies
AU - Wang, Nan
AU - Qin, Qiming
AU - Chen, Li
AU - Zhao, Shanshan
AU - Zhang, Chengye
AU - Hui, Jian
N1 - Publisher Copyright:
© 2016.
PY - 2016/10/1
Y1 - 2016/10/1
N2 - Petroleum exploration using natural source electromagnetic (EM) methods has recently increased due to the economic demand for obtaining high-resolution information about electrical parameter variations related to reservoirs. However, there are challenges present in using traditional EM methods. Regional geo-electrical structures inverted from induced EM signals are insufficient to determine the characteristics of reservoirs. In this study, we propose a natural source prospecting method to directly assess the depths and distributions of oil layers. This is accomplished by deriving electromagnetic radiation (EMR) signals caused by oil flow and reservoir fractures. The method has been validated by theoretical analyses and field measurements in Chepaizi Uplift, China. The modeling results show that Super-Low Frequency (SLF) magnetic amplitudes reveal stationary trends for various types of oil trap models. EMR anomalies, (distinguished from actual SLF magnetic signals) are noise-suppressed and enhanced using the ensemble empirical mode decomposition (EEMD) and the "DB4" wavelet transform. An empirical Frequency-Depth transformation model is developed to directly implement the depth sounding. EMR configurations at the corresponding depths of oil layers are recognized as the target of discovery i.e., reservoirs. The estimated depths of oil layers in producing wells are verified by the actual production, and the depth deviations of reservoirs are generally within a ±10% margin of error. This method is intended to be a viable tool in the accurate identification, delineation and dynamic monitoring of petroleum reservoirs.
AB - Petroleum exploration using natural source electromagnetic (EM) methods has recently increased due to the economic demand for obtaining high-resolution information about electrical parameter variations related to reservoirs. However, there are challenges present in using traditional EM methods. Regional geo-electrical structures inverted from induced EM signals are insufficient to determine the characteristics of reservoirs. In this study, we propose a natural source prospecting method to directly assess the depths and distributions of oil layers. This is accomplished by deriving electromagnetic radiation (EMR) signals caused by oil flow and reservoir fractures. The method has been validated by theoretical analyses and field measurements in Chepaizi Uplift, China. The modeling results show that Super-Low Frequency (SLF) magnetic amplitudes reveal stationary trends for various types of oil trap models. EMR anomalies, (distinguished from actual SLF magnetic signals) are noise-suppressed and enhanced using the ensemble empirical mode decomposition (EEMD) and the "DB4" wavelet transform. An empirical Frequency-Depth transformation model is developed to directly implement the depth sounding. EMR configurations at the corresponding depths of oil layers are recognized as the target of discovery i.e., reservoirs. The estimated depths of oil layers in producing wells are verified by the actual production, and the depth deviations of reservoirs are generally within a ±10% margin of error. This method is intended to be a viable tool in the accurate identification, delineation and dynamic monitoring of petroleum reservoirs.
KW - Electromagnetic radiation
KW - Ensemble empirical mode decomposition
KW - Frequency-Depth transformation
KW - Natural source
KW - Reservoir interpretation
KW - Super-Low Frequency
UR - http://www.scopus.com/inward/record.url?scp=84963979461&partnerID=8YFLogxK
U2 - 10.1016/j.petrol.2016.04.014
DO - 10.1016/j.petrol.2016.04.014
M3 - Article
AN - SCOPUS:84963979461
SN - 0920-4105
VL - 146
SP - 84
EP - 95
JO - Journal of Petroleum Science and Engineering
JF - Journal of Petroleum Science and Engineering
ER -