Search Results (16)

The N Oilfield is the first offshore extra-heavy oilfield developed using thermal recovery methods, adopting cyclic steam stimulation (CSS) and commissioned in 2022. The development of offshore heavy oil reservoirs is confronted with numerous technical and operational challenges. Key constraints include limited platform space, stringent economic thresholds for single-well production, and elevated operational risks, collectively contributing to significant uncertainties in project viability. For effective exploitation of the target oilfield, a comprehensive strategy was proposed, which consisted of effective artificial lifting, steam channeling and high water cut treatment. First, to achieve efficient artificial lifting of the extra-heavy oil, an integrated injection–production lifting technology using jet pump was designed and implemented. In addition, during the first steam injection cycle, challenges such as inter-well steam channeling, high water cut, and an excessive water recovery ratio were encountered. Subsequent analysis indicated that low-quality reservoir intervals were the dominant sources of unwanted water production and preferential steam channeling pathways. To address these problems, a suite of efficiency-enhancing technologies was established, including regional steam injection for channeling suppression, classification-based water shutoff and control, and production regime optimization. Given the significant variations in geological conditions and production dynamics among different types of high-water-cut wells, a single plugging agent system proved inadequate for their diverse requirements. Therefore, customized water control countermeasures were formulated for specific well types, and a suite of plugging agent systems with tailored properties was subsequently developed, including high-temperature-resistant N₂ foam, high-temperature-degradable gel, and high-strength ultra-fine cement systems. To date, regional steam injection has been implemented in 10 well groups, water control measures have been applied to 12 wells, and production regimes optimization has been implemented in 5 wells. Up to the current production round, no steam channeling has been observed in the well groups after thermal treatment. Compared with the pre-measurement stage, the average water cut per well decreased by 10%. During the three-year production cycle, the average daily oil production per well increased by 10%, the cumulative oil increment of the oilfield reached 15,000 tons, and the total crude oil production exceeded 800,000 tons. This study provides practical technical insights for the large-scale and efficient development of extra-heavy oil reservoirs in the Bohai Oilfield and offers a valuable reference for similar reservoirs worldwide. Full article

Radial drilling technology, which involves drilling multiple micro-horizontal wellbores radially from a main wellbore, can effectively expand the contact area between the wellbore and the reservoir, as well as the swept volume of thermal fluid. It is a promising technology for enhancing the efficiency of heavy oil thermal recovery. However, a systematic numerical simulation study on the application of this technology in the cyclic steam stimulation (CSS) development of heavy oil reservoirs is currently lacking. This paper establishes a numerical thermal recovery model for heavy oil reservoirs based on an unstructured grid modeling method, which can accurately describe the complex geometry of multi-layer, multi-branch radial wells. The model is discretized using the finite volume method and solved with a fully implicit method. Then, based on the geological parameters of a typical heavy oil reservoir, a comparative study was conducted on the production dynamics and physical field evolution of horizontal wells, single-layer radial wells, and dual-layer radial wells during the CSS process. The results indicate that, compared to conventional well types, dual-layer multi-branch radial wells can simultaneously inject steam into the upper and lower parts of the reservoir. This forms a more balanced and extensive three-dimensional heated body, significantly improving the planar sweep efficiency of heat and the uniformity of reserve recovery, thereby substantially increasing crude oil production and recovery factor. Compared to the horizontal well scenario, using dual-layer radial wells for CSS can increase cumulative oil production by 44.8%. Full article

Steam channeling significantly affects the production performance of cyclic steam stimulation (CSS) wells in offshore heavy oil reservoirs. However, there remains a lack of effective methods for evaluating the steam channeling severity between CSS wells in offshore heavy oil reservoirs. This study develops a novel evaluation model to quantitatively evaluate the steam channeling severity between CSS wells in offshore heavy oil reservoirs via the improved AHP-CRITIC (IAHP-CRITIC) method and the cloud model. The results indicated that, compared with the reservoir survey results for the three typical reservoirs, the accuracies of the results obtained by the AHP, CRITIC, AHP-CRITIC, and IAHP-CRITIC methods were 88%, 52%, 92%, and 100%, respectively. Therefore, the IAHP-CRITIC method was more reliable than the other methods in terms of calculating the indicator weights and evaluating the steam channeling severity between the CSS wells. The Lw7 and Lw12 in the L reservoir and Rw2, Rw3, and Rw6 in the R reservoir exhibited strong steam channeling. It is necessary to control the steam channeling of these CSS wells. This is the first study to report the evaluation of steam channeling severity between CSS wells in offshore heavy oil reservoirs. This study provides an effective model to quantitatively evaluate the steam channeling severity between CSS wells and offers valuable insights for the selection of effective strategies to control the steam channeling between CSS wells and enhance offshore heavy oil recovery. Full article

To overcome the production bottleneck induced by the high viscosity of extra-heavy oil and resolve the issues of limited efficiency in traditional thermal oil recovery methods (including cyclic steam stimulation (CSS), steam flooding, and steam-assisted gravity drainage (SAGD)) as well as the fragmentation of existing viscosity reducer evaluation systems, this study establishes a multi-dimensional evaluation system for the effectiveness of viscosity reducers, with stage-averaged remaining oil saturation as the core benchmarks. A “1D static → 2D dynamic → 3D synergistic” progressive sequential experimental design was adopted. In the 1D static experiments, multi-gradient concentration tests were conducted to analyze the variation law of the viscosity reduction rate of viscosity reducers, thereby screening out the optimal adapted concentration for subsequent experiments. For the 2D dynamic experiments, sand-packed tubes were used as the experimental carrier to compare the oil recovery efficiencies of ultimate steam flooding, viscosity reducer flooding with different concentrations, and the composite process of “steam flooding → viscosity reducer flooding → secondary steam flooding”, which clarified the functional value of viscosity reducers in dynamic displacement. In the 3D synergistic experiments, slab cores were employed to simulate the SAGD development process after multiple rounds of cyclic steam stimulation, aiming to explore the regulatory effect of viscosity reducers on residual oil distribution and oil recovery factor. This novel evaluation system clearly elaborates the synergistic mechanism of viscosity reducers, i.e., “chemical empowerment (emulsification and viscosity reduction, wettability alteration) + thermal amplification (steam carrying and displacement, steam chamber expansion)”. It fills the gap in the existing evaluation chain, which previously lacked a connection from static performance to dynamic displacement and further to multi-process synergistic adaptation. Moreover, it provides quantifiable and implementable evaluation criteria for steam–chemical composite flooding of extra-heavy oil, effectively releasing the efficiency-enhancing potential of viscosity reducers. This study holds critical supporting significance for promoting the efficient and economical development of extra-heavy oil resources. Full article

The steam assisted gravity drainage (SAGD) process requires high energy input to maintain the continuous expansion of the steam chamber for achieving high oil recovery. In the late stage of SAGD operation where the oil rate is low and the heat loss is high from a mature steam chamber, maintaining steam chamber pressure with a lower steam injection is the key to maintaining the economic oil-to-steam ratio (OSR). Both laboratory studies and field tests have demonstrated the effectiveness of adding a non-condensable gas (NCG) to the SAGD steam chamber for improving the overall thermal efficiency. In this study, a multi-well reservoir model was built based on the detailed geological description from an operating SAGD project area, which contains thick pay and top water. Grounded with the history matching of more than 20 years of production using CSS (cyclic steam stimulation) and SAGD as follow-up process, the model was applied to optimize the operating strategies for the late stage of SAGD production. The results from this study demonstrated that the co-injection of steam with CO₂ or the injection of CO₂ only has potential to improve the OSR and reduce emissions by more than 50% through the improvement in steam-saving and the storage of CO₂. The results from reservoir modeling indicate that, with the current volume of a steam chamber and an operating pressure of 4.0 MPa, about 55 sm³ of CO₂ could be sequestrated and utilized for producing 1.0 m³ of oil from this reservoir through the replacement of a steam injection with CO₂ in the late stage of SAGD operation. Full article

Cyclic steam stimulation is an effective thermal recovery method for heavy oil recovery. The key potential mechanism is the growth of the steam chamber after steam injection. Taking the LD5X heavy oil reservoir as an example, besides the interlayer developed in this area, the top water and bottom water distribute above and below the interlayer. These factors may have adverse effects on the development of the steam chamber, thus affecting the final heavy oil exploitation. In this work, our goal is to study the effects of interlayer permeability and well–interlayer distance on CSS performance (in the presence of top and bottom water). We developed a high-temperature-resistant interlayer. Based on the simulated interlayer, the field scale model was converted into a laboratory element model through the similarity criterion. In order to quantitatively evaluate the performance of steam stimulation, a thermal detector was used to measure the dynamic growth of the steam chamber and record the production data. The experimental results show that the self-made interlayer has high-temperature resistance, adjustable permeability, and little difference between the physical parameters and the target interlayer. During the cyclic steam stimulation process, the steam chamber presents two different stages in the presence of the top water area, namely the normal production stage and the top water discharge stage. The bottom water has little effect on the growth of the steam chamber. The small interlayer permeability, the increase in horizontal well–interlayer distance, and the existence of the interlayer will delay the top water leakage during steam stimulation. This study has reference significance for us to develop heavy oil resources with a top water barrier when implementing steam stimulation technology. Full article

Cyclic steam stimulation (CSS) is one of the main offshore heavy oil recovery methods used. Predicting the production of horizontal CSS wells is significant for developing offshore heavy oil reservoirs. Currently, the existing reservoir numerical simulation and analytical models are the two major methods to predict the production of horizontal CSS wells. The reservoir numerical simulation method is tedious and time-consuming, while the analytical models need many assumptions, decreasing models’ accuracy. Therefore, in this study, a novel methodology combining the particle swarm optimization algorithm (PA) and long short-term memory (LM) model was developed to predict the production of horizontal CSS wells. First, a simulation model was established to calculate the cumulative oil production (COP) of horizontal CSS wells under different well, geological, and operational parameters, and then the correlations between the calculated COP and parameters were analyzed by Pearson correlation coefficient to select the input variables and to generate the initial data set. Then, a PA-LM model for the COP of horizontal CSS wells was developed by utilizing the PA to determine the optimal hyperparameters of the LM model. Finally, the accuracy of the PA-LM model was validated by the initial data set and actual production data. The results showed that, compared with the LM model, the mean absolute percentage error (MAPE) of the testing set for the PA-LM model decreased by 4.27%, and the percentage of the paired points in zone A increased by 2.8% in the Clarke error grids. In addition, the MAPEs of the training set for the PA-LM and LM models stabilized at 267 and 304 epochs, respectively. Therefore, the proposed PA-LM model had a higher accuracy, a stronger generalization ability, and a faster convergence rate. The MAPEs of the actual and predicted COP of the wells B1H and B5H by the optimized PA-LM model were 8.66% and 5.93%, respectively, satisfying the requirements in field applications. Full article

To resolve the issues of the high porous medium flow resistance, low oil production rate, high oil decline rate, and low oil recovery factor for the cyclic steam stimulation (CSS) of horizontal wells in heavy oil reservoirs, the CSS method assisted by the electric heating (E-CSS) of horizontal wells was proposed in this study. Combining the heat from electric heating and steam during E-CSS, the analytical model of formation temperature rise was established for the three phases of electric-assisted CSS (i.e., injection, soaking, production), and physical experiments were carried out to compare the performance of conventional CSS and E-CSS. The experimental results were used to validate the analytical model and reveal the impact of the key electric heating mechanism on the horizontal CSS performance. Meanwhile, the typical well model was used to forecast the E-CSS potential. The results indicate that electric heating can achieve uniform heating in the steam injection phase, maintain heating around the wellbore in the soak phase, and reduce flow resistance and enhance oil output in the production phase. Forecasts of the typical well model indicate that electric heating can enhance the oil recovery factor by 9.4% and the oil-steam ratio from 0.14 to 0.23, implying a significant application potential in heavy oil reservoirs developed by horizontal CSS. Full article

Cyclic steam stimulation (CSS) is successfully applied to increase heavy oil recovery in heavy oil reservoirs in Bohai Bay, China. However, during the CSS processes, hydrogen sulfide (H₂S) was detected in some heavy oil reservoirs. The existing literature mainly focused on the H₂S generation of onshore heavy oil. There is no concrete experimental data available, especially about the level of H₂S generation during CSS of offshore heavy oil. In addition, there is still a lack of effective reaction kinetic models and numerical simulation methods to simulate H₂S generation during the CSS of offshore heavy oil. Therefore, this paper presents a case study from Bohai Bay, China. First, the laboratory aquathermolysis tests were conducted to simulate the gases that are produced during the CSS processes of heavy oil. The effects of the reaction temperature and time on the H₂S generation were studied. Then, a one-dimensional CSS experiment was performed to predict H₂S generation under reservoir conditions. A kinetic model for the prediction of H₂S generation during the CSS of heavy oil was presented. The developed model was calibrated with the experimental data of the one-dimensional CSS experiment at a temperature of 300 °C. Finally, a reservoir model was developed to predict H₂S generation and investigate the effects of soaking time, steam quality, and steam injection volume on H₂S generation during CSS processes. The results show that the H₂S concentration increased from 0.77 ppm in the first cycle to 1.94 ppm in the eighth cycle during the one-dimensional CSS experiment. The average absolute error between the measured and simulated H₂S production was 12.46%, indicating that the developed model can accurately predict H₂S production. The H₂S production increase with soaking time, steam quality, and steam injection volume due to the strengthened aquathermolysis reaction. Based on the reservoir simulation, the H₂S production was predicted in the range of 228 m³ to 2895 m³ within the parameters of this study. Full article

Production performance of heavy oil deposits in Xinjiang oilfield developed by vertical-well cyclic steam stimulation (CSS) is increasingly challenged by reservoir heterogeneity, which is comprised of original sedimental heterogeneity and steam-induced heterogeneity. In order to understand the impacts of sedimental heterogeneity and high-speed steam injection to steam conformance, and strategies to maximize steam swept volume, a series of experiments were designed and implemented. Three-tube coreflooding experiments were performed to study the steam displacement dynamics under heterogeneous conditions, and a high-temperature plugging agent was developed. The coreflooding experiments indicate that the injection conformance deteriorates once the steam breakthrough occurs in a high-permeability tube, leaving the oil in the medium and low permeability tubes being surpassed. The optimized plugging agent could resist high temperatures over 260 °C and its compressive strength was 13.14 MPa, which is higher than maximal steam injection pressure. The plugging rate of high permeability core was greater than 99.5% at 220–280 °C with a breakthrough pressure gradient over 25 MPa/m. The field test validated its profile improvement feasibility with cyclic oil, 217.6% of the previous cycle. The plugging agent optimized in this study has significant potential for similar heterogeneous reservoirs. Full article

Cyclic steam stimulation (CSS) is a typical enhanced oil recovery method for heavy oil reservoirs. In this paper, a new model for the productivity of a CSS well in multilayer heavy oil reservoirs is proposed. First, for the steam volume of each formation layer, it is proposed that the total steam injection volume will be split by the formation factor (Kh) for the commingled steam injection mode. Then, based on the equivalent flow resistance principle, the productivity model can be derived. In this model, the heavy oil reservoir is composed of a cold zone, a hot water zone, and a steam zone. Next, using the energy conservation law, the equivalent heating radius can be calculated with the consideration of the steam overlay. Simultaneously, a correlation between the threshold pressure gradient (TPG) and oil mobility is also applied for the productivity formula in the cold zone and the hot water zone. Afterward, this model is validated by comparing the simulation results with the results of an actual CNOOC CSS well. A good agreement is observed, and the relative error of the cumulative oil production is about 2.20%. The sensitivity analysis results indicate that the effect of the bottom hole pressure is the most significant, followed by the TPG, and the effect of the steam overlay is relatively slight. The formation factor can affect the splitting of the steam volume in each layer; thus, the oil production rate will be impacted. The proposed mathematical model in this paper provides an effective method for the prediction of preliminary productivity of a CSS well in a multilayer heavy oil reservoir. Full article

Canada’s in situ oil sands can help meet the global oil demand. Because of the energy-intensive extraction processes, in situ oil sands operations also play a critical role in meeting the global carbon budget. The steam oil ratio (SOR) is an indicator used to measure energy efficiency and assess greenhouse gas (GHG) emissions in the in situ oil sands industry. A low SOR indicates an extraction process that is more energy efficient and less carbon intensive. In this study, we applied machine learning methods for data-driven discovery to a public database, Petrinex, containing operating data from 2015 to 2019 extracted from over 35 million records for 20 in situ oil sands extraction operations. Two unsupervised machine learning methods, including clustering and association rules, showed that the cyclic steam stimulation (CSS) recovery method was less efficient than the steam-assisted gravity drainage (SAGD) recovery method. Chi-square tests showed a statistically significant association between the CSS recovery method and high SOR (p < 0.005). Two association rules suggested that the occurrence of non-condensable gas (NCG) co-injection produced a low SOR. Chi-square tests on the two rules identified a statistically significant relationship between gas co-injection and low SOR (p < 0.005). Association rules also indicated that there was no association between the production regions and SORs. For future in situ oil sands development, decision-makers should consider SAGD as the preferred method because it is less carbon intensive. Existing in situ oil sands projects and future development should explore the possibility of NCG co-injection with steam to reduce steam consumption and consequently reduce GHG emissions from the extraction processes. Full article

A novel workflow is presented for integrating fiber optic Distributed Temperature Sensor (DTS) data in numerical simulation model for the Cyclic Steam Stimulation (CSS) process, using an intelligent optimization routine that automatically learns and improves from experience. As the steam–oil relationship is the main driver for forecasting and decision-making in thermal recovery operations, knowledge of downhole steam distribution across the well over time can optimize injection and production. This study uses actual field data from a CSS operation in a heavy oil field in California, and the value of integrating DTS in the history matching process is illustrated as it allows the steam distribution to be accurately estimated along the entire length of the well. The workflow enables the simultaneous history match of water, oil, and temperature profiles, while capturing the reservoir heterogeneity and the actual physics of the injection process, and ultimately reducing the uncertainty in the predictive models. A novel stepwise grid-refinement approach coupled with an evolutionary optimization algorithm was implemented to improve computational efficiency and predictive accuracy. DTS surveillance also made it possible to detect a thermal communication event due to steam channeling in real-time, and even assess the effectiveness of the remedial workover to resolve it, demonstrating the value of continuous fiber optic monitoring. Full article

Heavy oil reservoirs with edge-bottom water represent a huge portion of the world’s reserves, and the effective development of such reservoirs with cyclic steam stimulation (CSS) is significant for the petroleum supply. However, the water cut of some CSS wells increases, and production decreases, with the increase of circulation turns. Discerning the source of the produced water is the basis of targeted treatment measures. In this paper, a new model is established for discriminating the source of produced water from CSS wells in edge-bottom water reservoirs. The model combines traditional hydrochemical characteristics analysis and factor analysis, and considers the quality change in injected water. The coefficient of formation water and injected water in produced water can thus be obtained. In addition, the normal distribution method is used to further divide interlayer water and edge-bottom water. The model was applied to a field case, and the results showed that one well was severely invaded by edge-bottom water. The results are consistent with field production performance, which further verifies the accuracy of the model. This model is of great significance for not only discriminating the source of produced water in an edge-bottom water reservoir, but also providing a basis for further the provision of further treatment measures. Full article

Most of the evaluations of thermal enhanced oil recovery (EOR) methods in numerical simulations mainly focus on the identification of recovery processes with the greatest potential to increase oil recovery. In some cases, the economic aspects of the EOR methods evaluated are also considered. However, these studies often lack the evaluation of the energy efficiency of the proposed methods as a strategy to support the selection of profitable recovery processes. Therefore, this study aimed to identify the potential of different hybrid cyclic steam stimulation (CSS, with flue gas, foam, nanoparticles, or solvents) methods based on a numerical simulation study using a radial model representative of a large heavy oil reservoir in the Middle Magdalena Basin, Colombia. The simulation results were used to estimate the benefit–cost (B/C) ratios and energy efficiency (EE) indices that can be used to screen and rank the hybrid CSS methods studied. When comparing different hybrid methods, it was found that CSS with nanoparticles or solvents performed better during the first two steam cycles (higher oil saturations). However, CSS with foam and flue gases showed higher incremental oil production (≥3564 bbls or 567 m³) during the sixth steam cycle. Based on an energy cost index (ECI = [(B/C) / EE]), CSS with foam outperformed (ECI ≈ 453) cyclic steam injection with flue gases (ECI ≈ 21) and solvents (ECI ≈ 0.1) evaluated during the sixth steam cycle. The results show that this methodology can be used to guide decision-making to identify hybrid CSS methods that can increase oil recovery in a cost-effective manner and provide an efficient energy balance. Full article