Sweet Spot Identification and Characterization of YingxiongLing Shale Oil Reservoir by Integrating 2D Nuclear Magnetic Resonance Data, Spectroscopy Data and Dielectric Data

Abstract

Abstract The lacustrine shale oil reservoir of the Ganchaigou Formation in the Qaidam plateau-type basin is extraordinarily complex. The lithology is a mixture of clay, quartz, and carbonate, and the porosity is usually less than 10%. With limited core data, the main pore types are not well understood, nor are the characterization and evaluation of the reservoir ‘sweet spot’, which has resulted in significant challenges for the current exploration effort. Identifying the sweet spot is particularly challenging just from conventional logs, where it has been extremely difficult to pinpoint layer selection and horizontal well landings, which is the main target for this study. In this paper we introduce a method for shale oil sweet-spot identification and evaluation by integrating spectroscopy, 2D nuclear magnetic resonance (NMR), and dielectric constant data. First, spectroscopy data were used to quantify the complex minerals inside, and then 2D NMR and dielectric data were combined for fluid identification. Water-filled porosity can be inverted from array dielectric constant, while T1 and T2 distribution measured by a 2D high-resolution nuclear magnetic logging tool can be classified into potential different signal sources with advanced blind source cluster analysis method. Subsequently, combining the results from dielectric constant and 2D NMR, we fine-tuned the interpretation models, and the fluid properties corresponding to different fluids can be identified and summed, such as movable oil, bound oil, bitumen, movable water, bound water, etc. Finally, the sweet-spot interval can be identified with the driving factors. Different from conventional reservoirs, in shale oil reservoirs, the content of movable oil, bitumen, or bound oil in unconventional reservoirs has a significant impact on the reservoir quality of the formation. The results from this formation showed that there is some relationship between effective porosity and dolomite content; however, the movable oil porosity changes significantly even within the same lithofacies. Hence, it is difficult to find one main rock type that has the best reservoir quality. In this situation, 2D NMR not only can it provide nuclear magnetic porosity, but also carry out fluid identification and formation fluid volume calculation, including bound water, bound oil, movable water, movable oil, etc. Using these key parameters, we can identify and evaluate the sweet spot with the highest movable oil porosity and lowest clay content directly and provide key guidance for test layer selection and horizontal well landing. 2D NMR provided a novel approach to evaluate these different components and help to identify the sweet spot of the reservoir. Besides, this method also provided a better way to quantify the oil saturation while the resistivity failed to do this due to lack of information of conductivity mechanism and electric parameters.