RESUMEN
Environmental awareness is receiving increasing attention in the petroleum industry, especially when associated with chemical agents applied in enhanced oil recovery (EOR) technology. The bio-based surfactant sodium cocoyl alaninate (SCA) is environmentally friendly and can be easily biodegraded, which makes it a promising alternative to traditional surfactants. Herein, the SCA surfactant is proposed as a foaming agent for enhanced oil recovery. Laboratory investigations on the surfactant concentration, foaming performance, microbubble characterization, interfacial tension, and foam-flooding of the traditional surfactants SDS and OP-10 have been conducted. In particular, the anti-salt abilities of these three surfactants have been studied, taking into consideration the reservoir conditions at Bohai Bay Basin, China. The results show that concentrations of 0.20 wt%, 0.20 wt% and 0.50 wt% for SCA, SDS and OP-10, respectively, can achieve optimum foaming ability and foaming stability under formation salinity conditions, and 0.20 wt% SCA achieved the best foaming ability and stability compared to 0.20 wt% SDS and 0.50 wt% OP-10. Sodium fatty acid groups and amino acid groups present in the SCA molecular structure have high surface activities under different salinity conditions, making SCA an excellent anti-salt surfactant for enhanced oil recovery. The microstructure analysis results showed that most of the SCA bubbles were smaller in size, with an average diameter of about 150 µm, and the distribution of SCA bubbles was more uniform, which can reduce the risk of foam coalescence and breakdown. The IFT value of the SCA/oil system was measured to be 0.157 mN m-1 at 101.5 °C, which was the lowest. A lower IFT can make liquid molecules more evenly distributed on the surface, and enhance the elasticity of the foam film. Core-flooding experimental results showed that a 0.30 PV SCA foam and secondary waterflooding can enhance oil recovery by more than 15% after primary waterflooding, which can reduce the mobility ratio from 3.7711 to 1.0211. The more viscous SCA foam caused a greater flow resistance, and effectively reduced the successive water fingering, leading to a more stable driving process to fully displace the remaining oil within the porous media. The bio-based surfactant SCA proposed in this paper has the potential for application in enhanced oil recovery in similar high-salt oil reservoirs.
RESUMEN
In view of the problems of low liquid production, a high proportion of high water cut wells, and poor development effect in the late stage of water flooding in the special sandstone reservoir of Niuquanhu "low permeability and medium viscosity crude oil", we carried out the research on hydrocarbon gas oil recovery and its influencing factors. First, the influence of different injected gas media on the physical properties of crude oil was analyzed. Second, the core displacement experiments of different gas injection media including CO2, CH4, and hydrocarbon gas were carried out by using the method of oil recovery comparison and optimization. Third, the indoor experimental study on the oil recovery of different influencing factors was carried out by using the method of controlling variables of influencing factors. Finally, the influence degree of different influencing factors on oil recovery was analyzed by a Spearman rank correlation coefficient analysis. The experimental results showed that the oil recovery of hydrocarbon gas is higher than that of CO2 and CH4, which were 57, 51, and 18% respectively. This is mainly because hydrocarbon gas is similar to the components of crude oil and is more easily dissolved in crude oil. The experimental results of influencing factors showed that the higher the content of C2-C4, the higher the oil recovery, and the content of C2-C4 will affect its dissolution with crude oil and its interaction with heavy component crude oil. The larger the permeability ratio, the lower the oil recovery, which was mainly due to the uneven distribution of injected gas in different regions. The higher the permeability, the lower the oil recovery, which was also due to the serious heterogeneity of the low permeability core of Niuquanhu; The results of Spearman rank correlation coefficient analysis based on different influencing factors and oil recovery showed that the order of influence of different factors on oil recovery was C2-C4 content > permeability ratio > permeability > back pressure > gas injection rate. In the development process of hydrocarbon gas injection, we should control the C2-C4 content, back pressure, and injection rate. The research in this study not only provides theoretical support for gas injection enhanced oil recovery technology in "low permeability and medium viscosity crude oil" reservoirs but also provides a new idea for the ranking of influencing factors.
RESUMEN
The conventional production technique employed for low-permeability tight reservoirs exhibits limited productivity. To solve the problem, an acetate-type supercritical carbon dioxide (scCO2) thickener, PVE, which contains a large number of microporous structures, was prepared using the atom transfer radical polymerization (ATRP) method. The product exhibited an ability to decrease the minimum miscibility pressure of scCO2 during a solubility test and demonstrated a favorable extraction efficiency in a low-permeability tight core displacement test. At 15 MPa and 70 °C, PVE-scCO2 at a concentration of 0.2% exhibits effective oil recovery rates of 5.61% for the 0.25 mD core and 2.65% for the 5 mD core. The result demonstrates that the incorporation of the thickener PVE can effectively mitigate gas channeling, further improve oil displacement efficiency, and inflict minimal damage to crude oil. The mechanism of thickening was analyzed through molecular simulation. The calculated trend of thickening exhibited excellent agreement with the experimental measurement rule. The simulation results demonstrate that the contact area between the polymer and CO2 increases in direct proportion to both the number of thickener molecules and the viscosity of the system. The study presents an effective strategy for mitigating gas channeling during scCO2 flooding and has a wide application prospect.
RESUMEN
Lost circulation events during drilling operations are known for their abruptness and are difficult to control. Traditional diagnostic methods rely on qualitative indicators, such as mud pit volume changes or anomalous logging curve patterns. However, these methods are subjective and rely heavily on empirical knowledge, resulting in delayed or inaccurate predictions. To address this problem, there is an urgent need to develop efficient methods for a timely and accurate lost circulation prediction. In this study, a novel approach is proposed by combining principal component analysis (PCA) and empirical analysis to reduce the dimensionality of the model data. This dimensionality reduction helps to streamline the analysis process and improve prediction accuracy. The predictive model also incorporates an improved fruit fly optimization algorithm (IFOA) in conjunction with support vector machine (SVM) techniques. The actual instances of lost circulation serve as the evaluation criteria for this integrated method. To overcome the challenges associated with irregular population distribution within randomly generated individuals, a tent map strategy is introduced to ensure a more balanced and representative sample. In addition, the model addresses issues such as premature convergence and slow optimization rates by employing a sine-cosine search strategy. This strategy helps to achieve optimal results and speeds up the prediction process. The improved prediction model demonstrates exceptional performance, achieving accuracy, precision, recall, and F1 scores of 96.8, 97, 96, and 96%, respectively. These results indicate that the IFOA-SVM approach achieves the highest accuracy with a reduced number of iterations, proving to be an efficient and fast method for predicting the lost circulation events. Implementation of this methodology in drilling operations can lead to improved efficiency, reliability, and overall performance.
RESUMEN
The high-temperature reservoir (105 °C) in the Liubei block of Jidong Oilfield, with severe longitudinal heterogeneity, has entered a high water-cut stage. After a preliminary profile control, the water management of the oilfield still faces serious water channeling problems. To strengthen water management, N2 foam flooding combined with gel plugging for enhanced oil recovery was studied. In this work, considering a high-temperature reservoir of 105 °C, a composite foam system and starch graft gel system with high temperature resistance were screened out, and displacement experiments in one-dimensional heterogeneous cores were carried out. Through the three-dimensional experimental model and numerical model of a 5-spot well pattern, physical experiments and numerical simulations were carried out respectively to study water control and oil increase. The experimental results showed that the foam composite system had good temperature resistance up to 140 °C and oil resistance up to 50% oil saturation and was helpful to adjust the heterogeneous profile in a high temperature of 105 °C. The starch graft gel system had good injection performance, with a solution viscosity of 18.15 mPa·s, and its gel strength could effectively seal the high-permeability layer, with a gel viscosity of 34950.92 mPa·s. The displacement test results showed that after a preliminary implementation of N2 foam flooding, N2 foam flooding combined with gel plugging could still improve oil recovery by 5.26%. Compared with preliminary N2 foam flooding, gel plugging could control the water channeling in the high-permeability zone near the production wells. The combination of foam and gel made N2 foam flooding and subsequent waterflooding divert to flow mainly along the low-permeability layer, which was conducive to enhance water management and improve oil recovery. This method can be used as an effective technology to manage similar heterogeneous reservoirs.
RESUMEN
Most of the oilfields are currently experiencing intermediate to late stages of oil recovery by waterflooding. Channels were created between the wells by water injection and its effect on the oil recovery is less. The use of water plugging profile control is required to control excessive water production from an oil reservoir. First, the well selection for profile control using the fuzzy evaluation method (FEM) and improvement by random forest (RF) classification model is investigated. To identify wells for profile control operation, a fuzzy model with four factors is established; then, a machine learning RF algorithm was applied to create the factor weight with high accuracy decision-making. The data source consists of 18 injection wells, with 70% of the well data being utilized for training and 30% for model testing. Following the fitting of the model, the new factor weight is determined and decisions are made. As a consequence, FEM selects 7 out of 18 wells for profile control, and by using the factor weight developed by RF, 4 out of 18 wells are chosen. Then, the profile control is conducted through a foam system proposed by laboratory experiments. A computer molding group numerical simulation model is created to profile the wells being selected by both methods, FEM and RF. The impact of foam system plugging on daily oil production, water cut, and cumulative oil production of both methods are contrasted. According to the study, the reservoir performed better when four wells were chosen by the weighting system developed by RF as opposed to seven wells that were chosen using the FEM model during the effective period. The weighting model developed by RF accurately increased the profile control wells' decision-making skills.
RESUMEN
The CO2 huff-n-puff process is an effective method to enhance oil recovery (EOR) and reduce CO2 emissions. However, its utilization is limited in a channeling reservoir due to early water and gas breakthrough. A novel starch graft copolymer (SGC) gel is proposed for treating the channels and assisting with the CO2 huff-n-puff process. Firstly, the bulk and dynamic performances of the SGC gel including rheology, injectivity and plugging ability are compared with the polymer gel in the laboratory. Then, 3D physical models with water channels are established to reveal the EOR mechanisms of gel assisted CO2 huff-n-puff. Several pilot tests of gel assisted CO2 huff-n-puff are also discussed in this paper. The bulk and dynamic experimental results show that although these two gelants have similar viscosities, the SGC gelant has a better injectivity compared with the polymer gelant. The SGC gel is predominantly a viscous solution, which make it easier to flow through the pore throats. The RF of the SGC gelant is only 0.58 times that of the polymer gelant. After the gelation, a 3D network-like gel with a viscosity of 174 267 mPa s can be formed using the SGC gelant. The RRF of the SGC gel is about three times that of the polymer gel, which shows that the SGC gel has a stronger plugging ability within the porous media. The 3D experimental results show that four cycles of gel assisted CO2 huff-n-puff can achieve an EOR of 11.36%, which is 2.56 times that of the pure CO2 huff-n-puff. After the channels are plugged by the SGC gel, the remaining oil of the near-wellbore area can be first extracted by CO2, and the oil of the deep formation can then be effectively displaced by the edge water. Pilot tests on five wells were conducted in the Jidong Oilfield, China, and a total oil production of 3790.86 m3 was obtained between 2016 and 2021. The proposed novel SGC gel is suitable for assisting with the CO2 huff-n-puff process, which is a beneficial method for further EOR in a water channeling reservoir.
RESUMEN
The major oil fields are currently in the middle and late stages of waterflooding. The water channels between the wells are serious, and the injected water does little effect. The importance of profile control and water blocking has been identified. In this paper, the decision-making technique for water shutoff is investigated by the fuzzy evaluation method, FEM, which is improved using a random forest, RF, classification model. A machine learning random forest algorithm was developed to identify candidate wells and to predict the well performance for water shutoff operation. A data set consisting of 21 production wells with three-year production history is used, where out of the mentioned well data, 70% of them are implemented for training and the remaining are used for testing the model. After fitting the model, the new weights for the factors are established and decision-making is made. Accordingly, 16 wells out of 21 wells are selected by the FEM where 8 wells out of 21 wells are selected by the new factor weight created by RF for water shutoff. A numerical simulation model is established to plug the selected wells by both methods after which the influence of plugging on water cut, daily oil production, and cumulative oil production is compared. The paper shows that the reservoir had a better performance after eight wells were selected using a new weighting system created by RF instead of the 16 wells that were selected using the FEM model. The paper also states that the new weighting model's accuracy improved the decision-making abilities of the wells.
RESUMEN
The CO2 huff-n-puff process is an effective method to enhance oil recovery; however, its utilization is limited in heterogenous edge-water reservoirs due to the severe water channeling. Accordingly, herein, a stable N2 foam is proposed to assist CO2 huff-n-puff process for enhanced oil recovery. Sodium dodecyl sulfate (SDS) and polyacrylamide (HPAM) were used as the surfactant and stabilizer, respectively, and 0.3 wt% of SDS + 0.3 wt% of HPAM were screened in the laboratory to generate a foam with good foamability and long foam stability. Subsequently, dynamic foam tests using 1D sand packs were conducted at 65 °C and 15 MPa, and a gas/liquid ratio (GLR) of 1 : 1 was optimized to form a strong barrier in high permeable porous media to treat water and gas channeling. 3D heterogeneous models were established in the laboratory, and N2-foam-assisted CO2 huff-n-puff experiments were conducted after edge-water driving. The results showed that an oil recovery of 13.69% was obtained with four cycles of N2-foam-assisted CO2 injection, which is twice that obtained by the CO2 huff-n-puff process. The stable N2 foam could temporarily delay the water and gas channeling, and subsequently, CO2 fully extracted the remaining oil in the low permeable zones around the production well. Pilot tests were conducted in 8 horizontal wells, and a total oil production of 1784 tons with a net price value (NPV) of $240 416.26 was obtained using the N2-foam-assisted CO2 huff-n-puff process, which is a profitable method for enhanced oil recovery in heterogenous reservoirs with edge water.