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The conventional methods for controlling excess water production in oil/gas wells can be classified on the basis of the mechanism (pore-blocking mechanism and relative permeability modification) used. Gel systems developed on the basis of a pore-blocking mechanism completely block the pores and stop the flow of both oil and water, whereas a relative permeability modifier (RPM) only restricts the flow of a single phase of the fluid. The gel working on the basis of the pore-blocking mechanism is known as a total blocking gel. An invert emulsified (PAM–PEI) polymer gel is a relative permeability modifier system. The same invert emulsion system is tested as a total blocking gel system in this research work. The dual-injection technique (1st injection and 2nd injection) was used for this purpose. In this research work, the emulsion system was tested at a temperature of 105 °C. The core sections with drilled holes and fractures were used for the core flooding experiments, representing a highly fractured reservoir. The developed emulsified gel system was characterized using a dilution test, an inverted bottle test, microscopic images, and FTIR images. The emulsified polymer gel was tested using a core flooding experiment. After the 2nd injection, the postflood medical CT and micro-CT images of the core sections clearly showed the presence of two different phases in the core section, i.e., the oil phase and the gel phase. The core flooding experiment result indicates that the gel formed after the 2nd injection of the emulsion system can withstand a very high differential pressure, i.e., above 2000 psi. The gel did not allow any oil or water to be produced. Hence, the developed emulsified polymer gel system with the help of a dual-injection technique can be efficiently used as a total blocking gel for high-temperature reservoirs.

Up to 2010, 44.55% of 312 EOR's project for light oil implemented around the world in sandstone reservoirs were come from continuous miscible gas CO2 injection which contributed to an incremental Recovery Factor (RF) of about 34.5% for less than 10 years of production period. This fact has triggered many oil industries to apply this potential and proven technogy for their assets. This potential comes with the needs of having a robust tool to forecast additional recovery due to CO2 injection. This work focuses to development of predictive model using artificial neural network (ANN). More than 6000 series of input-output parameters for ANN training and validation/testing data are extracted from numerical reservoir simulator of 1/8 of five-spot pattern models. The models are set as combination of reservoir geometry, rock, fluid and well operating condition parameters within the range of CO2 EOR screening criteria. The main objective of this work is to find the best ANN architecture/model which accurately matches reservoir simulation results, especially the relationship of RF, total volume of injected CO2 (GI) and the reservoir characteristics and well operating conditions. Trial and error of ANN architectures and parameters are done on number of hidden layers, number of neurons for each hidden layer, learning rate (LR) value, and momentum constant (MC) with minimization algorithm (Lavenberg-Marquardt) in Feed-Forward Back Propagation (FFBP) schemes under log-sigmoid transfer function. An optimum result of ANN model is achieved with an architecture of 18-26-11-2. The relative error of RF and GI of the ANN model are within range of 3 to 10% respectively. A better average relative error of RF and GI of 2.8% and 4.15% respectively are obtained after removing the outliers (unrealistic combinations of input data) from training process of the ANN model. Furthermore, it is clearly found that oil viscosity plays the most the important factor in CO2 EOR method.

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This study provides a workflow and preliminary estimations of the estimated ultimate recovery (EUR) volumes for natural gas and condensate liquids in the Tuwaiq Mountain Formation, the principal target in the Jafurah Field development project in Saudi Arabia. The strategic need for the field development is reviewed and the field characteristics are outlined based on public data sources complemented with data from analogous reservoirs. The target zone in the Jafurah Basin is a carbonaceous shale, being developed with up to 10,000-ft-long multistage-fractured laterals with 30 ft perforation cluster spacing and an assumed typical 1250 ft well spacing. The field will come on stream in 2024, when the gas-gathering pipeline system, natural gas processing plant, and underground gas storage facilities will all be in place. The range of uncertainties in the key reservoir parameters is taken into account to estimate preliminary EUR volumes (P90, P50, and P10) for both gas and condensates. Based on the present and prior EUR estimations, it can be concluded that the Jafurah Basin comprises one of the largest unconventional field development projects outside of North America.