Enhanced oil recovery (EOR) and maximizing recovery from declining production fields remain a challenge in the offshore industry. The challenge is to find an EOR method that is both technically and economically feasible considering the high capital and operating costs in the offshore environment. The goal of this work was to conduct a simple cost-benefit analysis based on a technical, facility, and economical screening of chemical EOR methods applicable to the offshore. Offshore Newfoundland, Canada is used as a base case as it represents a challenging geographical environment. The reservoir properties are good, based on volumetrics and characteristics, but the fields are located over 300 km offshore in a harsh environment where operational costs are high. A data mining approach was used for the EOR screening process. Data from over one thousand core flooding experiments investigating various chemical EOR methods, including surfactant, polymer, alkaline-surfactant (AS), alkaline-surfactant-polymer (ASP), nanoparticle, and low salinity water injection (LSWI), were collected. Factors with the greatest influence on the performance of a given EOR method were statistically examined and discretized. The ranges of recovery factor, rock type, chemical concentrations, and the most commonly used chemicals are presented in this review paper. Economic factors examined included capital expenditures (CAPEX) and the operating cost of production (OPEX). Benefits are found to be strongly related to oil production and Brent crude oil forecasts. Sensitivity studies of the recovery factor ranges with the different chemical concentrations, net present values (NPV), and the influence of the inflation were all taken into consideration. Two different injection plans were considered: injection from day one of production, and injection after secondary production. The highest CAPEX and OPEX were calculated for the ASP method, whereas LSWI resulted in the lowest. The results indicate that most of the chemical EOR methods could be economically successful, however, the timing of implementation will affect the potential benefits. If high recovery and low chemical concentrations are considered, ASP flooding is the most successful chemical EOR method when injecting from day one. However, if the EOR method starts after a decline in production, surfactant flooding proves more beneficial, regardless of the scenario considered. This paper presents a systematic approach to chemical EOR screening, combining available technical data using a data analytics approach with economic and technical uncertainty.

Gas permeability, which is measured mainly through gas permeability experiments, is a critical technical index in many engineering fields. In this study, permeability is firstly calculated based on information from a digital image and an improved permeability prediction model. The calculated results are experimentally verified. Subsequently, a selfdeveloped image-processing program is used to extract feature parameters from a scanning electron microscopy image. Meanwhile, an extreme learning machine algorithm is used to input the image feature parameters obtained using the image-processing program into the extreme learning machine algorithm for machine learning. Additionally, we compare several typically used machine learning algorithms, which confirmed the reliability and accuracy of our algorithm. The best activation function can be obtained by comparing the predicted permeability using an appropriate number of neuron nodes. Experimental results show that the program can accurately identify the features of the microscopy image. Combining the program with an extreme learning machine neural network algorithmgas permeability results to be obtained with high accuracy. This method yields good predictions of permeability in certain cases and has been adapted to other geomaterials.

Low salinity water injection (LSWI) is considered to be more cost-effective and has less environmental impacts over conventional chemical Enhanced Oil Recovery (EOR) methods. CO2 Water-Alternating-Gas (WAG) injection is also a leading EOR flooding process. The hybrid EOR method, CO2 low salinity (LS) WAG injection, which incorporates low salinity water into CO2 WAG injection, is potentially beneficial in terms of optimizing oil recovery and decreasing operational costs. Experimental and simulation studies reveal that CO2 LSWAG injection is influenced by CO2 solubility in brine, brine salinity and composition, rock composition, WAG parameters, and wettability. However, the mechanism for increased recovery using this hybrid method is still debatable and the conditions under which CO2 LSWAG injection is effective are still uncertain. Hence, a comprehensive review of the existing literature investigating LSWI and CO2 WAG injection, and laboratory and simulation studies of CO2 LSWAG injection is essential to understand current research progress, highlight knowledge gaps and identify future research directions. With the identified research gap, a core-scale simulation study on hysteresis effect in CO2 LSWAG injection is carried out. The results indicate different changing trend in oil recovery due to the impact of salinity on hysteresis and excluding of hysteresis effect in CO2 LSWAG injection simulation and optimization might lead to significant errors.

A preliminary enhanced oil recovery (EOR) screening was completed for the Ben Nevis Formation, Hebron Field, offshore Canada. Polymer flooding was determined to be the most viable methodology based on the oil and reservoir properties and known challenges with respect to sourcing potential injection gas. Digital image analysis and microscopic petrographic analysis were applied to investigate the pore system characterization in Ben Nevis formation sandstone cores, which were subjected to an experimental polymer injection at 62 °C. Polymer Flopaam 5115 delivered the best performance in terms of oil recovery irrespective of the flooding sequence or permeability facies. Initial grain size before flooding has a profound impact on oil displacement efficiency. Pore network analyses before and after flooding indicate that the movement of fine grains potentially affects porosity postflooding, depending on the permeability facies.

In this paper, a THMC multi-field coupling triaxial cell was used to systematically study the evolution of gas permeability and the deformation characteristics of sandstone. The effects of confining pressure, axial pressure and air pressure on gas permeability characteristics were fully considered in the test. The gas permeability of sandstone decreases with increasing confining pressure. When the confining pressure is low, the variation of gas permeability is greater than the variation of gas permeability at high confining pressure. The gas injection pressure has a significant effect on the gas permeability evolution of sandstone. As the gas injection pressure increases, the gas permeability of sandstone tends to decrease. At the same confining pressure, the gas permeability of the sample during the unloading path is less than the gas permeability of the sample in the loading path. When axial pressure is applied, the axial stress has a significant influence on the permeability evolution of sandstone. When the axial pressure is less than 30 MPa, the gas permeability of the sandstone increases as the axial pressure increases. At axial pressures greater than 30 MPa, the permeability decreases as the axial pressure increases. Finally, the micro-pore/fracture structure of the sample after the gas permeability test was observed using 3D X-ray CT imaging.