S. A. Hasheminejad; K. Ahmadi
Abstract
This paper aims to optimally determine petrophysical facies according to well log data. Using the automatic classification method of K-NN (K-Nearest Neighbours), petrophysical facies can be determined even though not optimally. For optimal determination of facies, the K-NN method is combined with FastICA ...
Read More
This paper aims to optimally determine petrophysical facies according to well log data. Using the automatic classification method of K-NN (K-Nearest Neighbours), petrophysical facies can be determined even though not optimally. For optimal determination of facies, the K-NN method is combined with FastICA (Fast Independent Component Analysis) and DCT (Discrete Cosine Transform) methods. This increases the success rate of the K-NN method. It also brings about optimal determination of petrophysical facies after which modelling and description of hydrocarbon reservoirs can be done. The research is performed in two different ways: In the first approach, the FastICA method is applied to data and then classified by the K-NN method. In the second approach, FastICA and DCT methods are applied to data and then classified by the K-NN method. Finally, the success rate of classification by the K-NN method is evaluated in both approaches to optimally determine petrophysical facies. Such evaluations indicate that application of the second method to data significantly enhances the success rate of the classification by the K-NN method, thereby leading to optimal determination of petrophysical facies, which is the very aim of this study. The utilized data including sonic log (DT), gamma rays (SGR), density (FDC or RHOB), neutron porosity (CNL or NPHI), and deep induction logs (ILD), belongs to the Marun oil field in southern Iran.
Soheila Roshanzamir; K. Ahmadi
Abstract
Reservoir geophysics studies have playeda significant role in exploration and production activities during the last decades. These techniques often try to identify the lithology and fluid content of the reservoir by utilization of pre-stack seismic data. The most effective type of these studies is performed ...
Read More
Reservoir geophysics studies have playeda significant role in exploration and production activities during the last decades. These techniques often try to identify the lithology and fluid content of the reservoir by utilization of pre-stack seismic data. The most effective type of these studies is performed in sandstone reservoirs,in which shear sonic logs increase the quality of the results. In this study, Amplitude Versus Offset (AVO) technique is applied in one of the sandstone reservoirs in the Persian Gulf. The applied methodology is based on modeling of seismic responses with different scenarios of fluid saturations in order to identify,using rock physics models, theseismic behavior of the reservoir in wells lacking shear logs. To achieve this goal, petrophysical interpretations of well data and reservoir parameters were integrated into a rock physics model, which eventually helped to recognize the seismic attributes sensitive to fluid content of the reservoir. In addition, calculation of pre-stack seismic attributes data led us to discriminate accurately the gas-oil contact. The comparison of the AVO study results with petrophysical evaluation results shows that AVO method results are very reliable and precise in the study area.
