Optimization of CO2 Injection Huff and Puff Process in Shale Reservoirs Based on NMR Technology

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Abstract
The pore mobilization characteristics of CO2 when in shale reservoirs is an important indicator for evaluating the effectiveness of its application for enhanced recovery in shale reservoirs, and it is important to develop a comprehensive set of physical simulation methods that are consistent with actual field operations. This has underscored the need for efficient development techniques in the energy industry. The huff-n-puff seepage oil recovery method is crucial for developing tight oil reservoirs, including shale oil. However, the small pore size and low permeability of shale render conventional indoor experiments unsuitable for shale oil cores. Consequently, there is a need to establish a fully enclosed experimental method with a high detection accuracy to optimize the huff and puff process parameters. The NMR technique identifies oil and gas transport features in nanogaps, and in this study, we use low-field nuclear magnetic resonance (NMR) online displacement technology to conduct CO2 huff and puff experiments on shale oil, covering the gas injection, well stewing, and production stages. After conducting four rounds of huff-n-puff experiments, key process parameters were optimized, including the simmering time, huff-n-puff timing, number of huff-n-puff rounds, and the amount of percolant injected. The findings reveal that as the number of huff-n-puff rounds increases, the time required for well stabilization decreases correspondingly. However, the enhancement in recovery from additional huff-n-puff rounds becomes negligible after three rounds, showing only a 1.16% improvement. CO2 re-injection is required when the pressure falls to 70% of the initiaformation pressure to ensure efficient shale oil well development. This study also indicates that the most economically beneficial results are achieved when the injection volume of the huff-n-puff process is 0.44 pore volumes (PVs).
Funding Information
  • National Science and Technology Major Project (2016ZX05060004)

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