An Experimental Study of Cyclic Gas Injection to Improve Shale Oil Recovery

Author(s):  
T.D. Gamadi ◽  
J.J. Sheng ◽  
M.Y. Soliman
2021 ◽  
Author(s):  
Hilario Martin Rodriguez ◽  
Yalda Barzin ◽  
Gregory James Walker ◽  
Markus Gruenwalder ◽  
Matias Fernandez-Badessich ◽  
...  

Abstract This study has double objectives: investigation of the main recovery mechanisms affecting the performance of the gas huff-n-puff (GHnP) process in a shale oil reservoir, and application of optimization techniques to modelling of the cyclic gas injection. A dual-permeability reservoir simulation model has been built to reproduce the performance of a single hydraulic fracture. The hydraulic fracture has the average geometry and properties of the well under analysis. A history match workflow has been run to obtain a simulation model fully representative of the studied well. An optimization workflow has been run to maximize the cumulative oil obtained during the GHnP process. The operational variables optimized are: duration of gas injection, soaking, and production, onset time of GHnP, injection gas flow rate, and number of cycles. This optimization workflow is launched twice using two different compositions for the injection gas: rich gas and pure methane. Additionally, the optimum case obtained previously with rich gas is simulated with a higher minimum bottom hole pressure (BHP) for both primary production and GHnP process. Moreover, some properties that could potentially explain the different recovery mechanisms were tracked and analyzed. Three different porosity systems have been considered in the model: fractures, matrix in the stimulated reservoir volume (SRV), and matrix in the non-SRV zone (virgin matrix). Each one with a different pressure profile, and thus with its corresponding recovery mechanisms, identified as below: Vaporization/Condensation (two-phase system) in the fractures.Miscibility (liquid single-phase) in the non-SRV matrix.Miscibility and/or Vaporization/Condensation in the SRV matrix: depending on the injection gas composition and the pressure profile along the SRV the mechanism may be clearly one of them or even both. Results of this simulation study suggest that for the optimized cases, incremental oil recovery is 24% when the gas injected is a rich gas, but it is only 2.4% when the gas injected is pure methane. A higher incremental oil recovery of 49% is obtained, when injecting rich gas and increasing the minimum BHP of the puff cycle above the saturation pressure. Injection of gas results in reduction of oil molecular weight, oil density and oil viscosity in the matrix, i.e., the oil gets lighter. This net decrease is more pronounced in the SRV than in the non-SRV region. The incremental oil recovery observed in the GHnP process is due to the mobilization of heavy components (not present in the injection gas composition) that otherwise would remain inside the reservoir. Due to the main characteristic of the shale reservoirs (nano-Darcy permeability), GHnP is not a displacement process. A key factor in success of the GHnP process is to improve the contact of the injected gas and the reservoir oil to increase the mixing and mass transfer. This study includes a review of different mechanisms, and specifically tracks the evolution of the properties that explain and justify the different identified mechanisms.


Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3961
Author(s):  
Haiyang Yu ◽  
Songchao Qi ◽  
Zhewei Chen ◽  
Shiqing Cheng ◽  
Qichao Xie ◽  
...  

The global greenhouse effect makes carbon dioxide (CO2) emission reduction an important task for the world, however, CO2 can be used as injected fluid to develop shale oil reservoirs. Conventional water injection and gas injection methods cannot achieve desired development results for shale oil reservoirs. Poor injection capacity exists in water injection development, while the time of gas breakthrough is early and gas channeling is serious for gas injection development. These problems will lead to insufficient formation energy supplement, rapid energy depletion, and low ultimate recovery. Gas injection huff and puff (huff-n-puff), as another improved method, is applied to develop shale oil reservoirs. However, the shortcomings of huff-n-puff are the low sweep efficiency and poor performance for the late development of oilfields. Therefore, this paper adopts firstly the method of Allied In-Situ Injection and Production (AIIP) combined with CO2 huff-n-puff to develop shale oil reservoirs. Based on the data of Shengli Oilfield, a dual-porosity and dual-permeability model in reservoir-scale is established. Compared with traditional CO2 huff-n-puff and depletion method, the cumulative oil production of AIIP combined with CO2 huff-n-puff increases by 13,077 and 17,450 m3 respectively, indicating that this method has a good application prospect. Sensitivity analyses are further conducted, including injection volume, injection rate, soaking time, fracture half-length, and fracture spacing. The results indicate that injection volume, not injection rate, is the important factor affecting the performance. With the increment of fracture half-length and the decrement of fracture spacing, the cumulative oil production of the single well increases, but the incremental rate slows down gradually. With the increment of soaking time, cumulative oil production increases first and then decreases. These parameters have a relatively suitable value, which makes the performance better. This new method can not only enhance shale oil recovery, but also can be used for CO2 emission control.


2014 ◽  
Author(s):  
T.D. Gamadi ◽  
J.J. Sheng ◽  
M.Y. Soliman ◽  
H. Menouar ◽  
M.C. Watson ◽  
...  

2016 ◽  
Vol 19 (02) ◽  
pp. 350-355 ◽  
Author(s):  
T.. Wan ◽  
J. J. Sheng ◽  
M. Y. Soliman ◽  
Y.. Zhang

Summary The current technique to produce shale oil is to use horizontal wells with multistage stimulation. However, the primary oil-recovery factor is only a few percent. The low oil recovery and abundance of shale reservoirs provide a huge potential for enhanced oil-recovery (EOR) process. Well productivity in shale oil-and-gas reservoirs primarily depends on the size of fracture network and the stimulated reservoir volume (SRV) that provides highly conductive conduits to communicate the matrix with the wellbore. The fracture complexity is critical to the well-production performance, and it also provides an avenue for injected fluids to displace the trapped oil. However, the disadvantage of gasflooding in fractured reservoirs is that injected fluids may break through to production wells by means of the fracture network. Therefore, a preferred method is to use cyclic gas injection to overcome this problem. In this paper, we use a numerical-simulation approach to evaluate the EOR potential in fractured shale-oil reservoirs by cyclic gas injection. Simulation results indicate that the stimulated fracture network contributes significantly to the well productivity by means of its large contact area with the matrix, which prominently enhances the macroscopic sweep efficiency in secondary cyclic gas injection. In our previous simulation work, the EOR potential was evaluated in hydraulic planar-traverse fractures without considering the propagation of a natural-fracture network. In this paper, we examine the effect of fracture networks on shale oilwell secondary-production performance. The impact of fracture spacing and stress-dependent fracture conductivity on the ultimate oil recovery is investigated. The results presented in this paper demonstrate that cyclic gas injection has EOR potential in shale-oil reservoirs. This paper focuses on evaluating the effect of fracture spacing, the size of the fracture network, fracture connectivity (uniform and nonuniform), and stress-dependent fracture-network conductivity on well-production performance of shale-oil reservoirs by secondary cyclic gas injection.


2021 ◽  
Vol 48 (3) ◽  
pp. 702-712
Author(s):  
Dongjiang LANG ◽  
Zengmin LUN ◽  
Chengyuan LYU ◽  
Haitao WANG ◽  
Qingmin ZHAO ◽  
...  

2017 ◽  
Vol 31 (5) ◽  
pp. 4951-4965 ◽  
Author(s):  
Nasser M. Al Hinai ◽  
A. Saeedi ◽  
Colin D. Wood ◽  
R. Valdez ◽  
Lionel Esteban

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