Cumulative Oil Research Articles

An improved coupled flow-geomechanical model for cyclic steam stimulation

Considering the pore deformation and permeability changes during dilation-recompaction in cyclic steam stimulation (CSS), an existing geomechanical model is improved and thermo-mechanically coupled with the flow equations to form a coupled flow-geomechanical model. The impacts of dilation-recompaction parameters can be quantified through sensitivity analysis and uncertainty assessment utilizing the synergy between Latin hypercube designs and response surface methodology. The improved coupled flow-geomechanical model allows a more reasonable history-matching of steam injection pressure and volume and oil/water production volume. In both the linear and quadratic models, the rise in recompaction pressure has the most significant effect on the rise in the volumes of steam injection and water production, both rock compressibility and recompaction pressure are positively correlated with steam injectivity and oil/water production, and the dilation pressure is negatively correlated with steam injectivity and oil/water production. In the linear model, dilation pressure has the most significant negative impact on the cumulative oil production, and compressibility and recompaction pressure are positively correlated with oil production. In the quadratic model, the rise in recompaction pressure has the most significant effect on the rise in the cumulative volumes of oil/water production and steam injection. The interactions between the dilation/recompaction pressures and spongy-rock compressibility negatively affect the cumulative volumes of oil/water production and steam injection.

Applying a deep-learning surrogate model to simulate and compare achievable oil recovery by different waterflood scenarios

Reservoir pressure depletion is a critical aspect leading to declined oil production. Water flooding becomes mandatory to increase the recovery efficiency from certain reservoirs. Establishing well placements, injection rates, and injection schedules enables improved fluid displacement in such reservoirs. Standard reservoir simulators are widely used to provide near-optimal scenarios for maximizing oil recovery. Such reservoir simulations involved numerous iterations and required significant computational effort. Also, the conventional machine learning methods provide a relatively high uncertainty to predict the considered problem. In this context, a deep-learning surrogate model comprising long short-term memory networks and densely connected networks is proposed to predict cumulative oil production using various waterflood injection well patterns, injection rates, and injection period information. The relevance test clarifies that the oil recovery mainly controls by water injection duration and injection pattern. A total of 1485 data records are considered to validate the model’s performance, demonstrating less than 3.5% absolute average relative error and a prediction versus actual value regression coefficient of 0.99989. In addition, the prediction accuracy of the proposed deep-learning model is also shown to outperform two well-known traditional machine-learning models (i.e. artificial neural networks and support vector regressions).

A coupled matrix-fracture productivity calculation model considering low-velocity non-Darcy flow in shale reservoirs

The flow behavior of shale reservoirs is extremely complex. The mainly used development method of large-scale volume fracturing of horizontal wells is associated with a series of problems such as low productivity in general, fast decrease in productivity, and difficulty to increase productivity. Therefore, it is necessary to evaluate the productivity of shale oil wells and determine the key control factors. Considering low-velocity non-Darcy flow, this paper establishes an analytical solution model for productivity calculation of multi-fracture shale oil horizontal wells with coupled matrix-fracture flow. Calculating the oil production rate by considering low-velocity non-Darcy flow in shale oil reservoirs obtains values closer to the actual oil production rate on site. The average relative error of the oil production rate of the H8 shale oil well is 4.27%. The average relative error of the oil production rate of the TMS shale oil wells is 34.97%, which exceeds the rate of the semi-analytical model by 47.84%. Sensitivity analysis shows that the oil production rate of multi-fracture shale oil horizontal wells is most sensitive to fracture cluster spacing and flowing bottom hole pressure. With decreasing fracture cluster spacing and flowing bottom hole pressure, both the matrix pressure gradient and the apparent permeability of the matrix increase. These increases not only increase the oil production rate but also reduce the influence of the non-Darcy effect on the oil production rate caused by boundary effect. In addition, the limits of the impact of non-Darcy effects caused by boundary effect on oil production rate have been clarified. The results enable not only the prediction of the oil production rate, cumulative oil production, and recovery factor of multi-fracture horizontal shale oil wells, but also the finding of the shale oil sweet spot according to the influence of matrix permeability and crude oil viscosity on the oil production rate.

Data-driven analysis of using flow control devices and extended reach wells on SAGD well performance

The industry's current trend to reduce Capital Expenditures (CapEx) and to minimize the environmental impacts has led to drilling long lateral wells and developing key innovative tools like Flow Control Devices (FCDs). This study analyzed the relative performance of various FCD deployments using data from major Steam-Assisted Gravity Drainage (SAGD) projects in Western Canada, spanning from 1997 to mid-2022. The goal is to investigate the impact of FCD deployment and increasing the lateral length on SAGD well performance in terms of boosting oil produciton and lowering cumulative Steam Oil Ratio (cSOR).This paper utilizes a normalization technique to evaluate the production history of wells, considering geological and operational parameters. Following our confidential conversations with experts in the industry, wells exceeding 850 m in lateral lengths are labeled as “long”, while those below 850 m are labeled as “short”. Eventually, normalized oil production and cSOR for all wells are analyzed. A comparison is made between short and long wells that are completed or retrofitted with FCDs, giving an insight into the role of completion design on the relative performance of SAGD wells.Reservoir thickness and reservoir quality are assessed for each well using contour maps and Gamma Ray (GR) log images. These images are digitized using image processing codes developed in our study. On average, across all projects, wells equipped with FCDs produced up to 52% more normalized oil than those without FCDs, and cSOR decreased to 18%. Long wells, on average, had lateral lengths 38% greater than short wells and produced 18% more normalized oil than all short wells. When comparing long wells with and without FCDs, the normalized oil production is improved by up to 36%, and cSOR is lowered by up to 17%. Furthermore, comparing long wells with FCDs to short wells without FCDs reveals that the normalized oil production is improved by up to 96%, and cSOR is lowered by up to 26%. The results highlight the synergistic benefits of combining longer wells with FCDs to improve normalized oil production and cSOR. The historical production analysis show that installing FCDs is the key enabler and an innovative strategy to increase productivity, reduce cSOR, and make longer wells more productive.The findings indicate that FCDs might increase oil production and decrease cSOR for SAGD well-pad developments, allowing operators to reduce Greenhouse Gas (GHG) emissions intensity. The findings may be used to examine paradigm shifts in the development of heavy oil deposits as technology advances while keeping the project economics into account.

A Hybrid Analytical and Data-Driven Approach for Improved Prediction of Recovery Performance in Tight Oil Reservoirs

Summary The heterogeneity of tight reservoirs, along with their complex geologic characteristics and the diverse completion practices used, presents challenges in developing accurate models to forecast the productivity for multifractured horizontal wells (MFHWs) completed in these reservoirs. This paper introduces a new early-time diagnostic tool that leverages early-time two-phase flowback data to forecast long-term productivity and evaluate completion efficiency. To achieve this, two novel models were developed. The first model, the water/oil-ratio model (WORM), uses a hybrid analytical and data-driven approach to describe the observed log-linear relationship between water/oil ratio (WOR) and load recovery (amount of fracturing water produced back after hydraulic fracturing operations) as an analogy to the log-linear relationship between the water/oil relative permeability ratio and water saturation. Next, a neural network is used to couple WORM parameters with key petrophysical properties to analyze the impact of fracture and formation properties on WOR performance, predict WOR as a function of load recovery, forecast ultimate load recovery, and estimate effective fracture volume and initial water saturation in fracture. The second model, the cumulative oil production model (COPM), is a data-driven model that predicts oil production as a function of load recovery during the matrix-dominated flow regime. The application of WORM and COPM on Niobrara and Codell formation wells showed that Codell wells generally exhibit better load recovery and larger effective fracture volume compared with Niobrara wells, but both formations exhibit similar oil recovery performance, indicating independent flow regimes within the effective fractures. The effective fracture volume estimated by WORM was validated against the estimated volume from recorded microseismic events. The results also showed that using the same completion practice to achieve a similar effective fracture volume in child wells does not necessarily lead to similar oil productivity. This paper introduces a holistic workflow that links early two-phase flowback data with well productivity and completion efficiency and is anticipated to aid petroleum engineers in optimizing hydraulic fracturing operations.

Robust waterflood optimization under geological uncertainties using streamline-based well pair efficiencies and assimilated models

Effective management of waterflooding requires optimization of injection and production rates. However, nominal optimization methods based on a single realization can result in suboptimal hydrocarbon recovery and sweep efficiency due to reservoir heterogeneity. To account for geological uncertainties, this paper proposes a streamline-based robust rate optimization that iteratively adjusts well rates of each realization using a joint well pair rate multiplier calculated from optimal interpolation method. This optimization process is applied over time intervals until the end of field life. The effective and robustness of this approach are validated using a 2D synthetic case and then applied to Brugge benchmark case. For each application, we generate 100 history-matched geological realizations, evenly split into 50 for training and 50 for testing purposes. Robust optimization is employed on the complete training dataset to derive an optimal schedule that maximizes the expected oil across all realizations. Simultaneously, nominal optimization is individually applied to each training realization to establish an optimal schedule specific to each instance. Subsequently, both the robust optimization schedule and the nominal optimization schedules are applied to the testing dataset to assess and compare their effectiveness. Results indicate that the streamline-based rate allocation optimization effectively adjusts well rates based on well-pair efficiency. The robust optimized schedule takes into account geological uncertainties and enhances cumulative oil production, even if it doesn't consistently outperform the nominal optimized schedules. Overall, this approach provides an effective way to optimize waterflooding management under geological uncertainties.

Impacts of proppant distribution on development of tight oil reservoirs with threshold pressure gradient

Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity. Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit, Ordos Basin of China, we presented an integrated workflow to investigate how (1) proppant placement in induced fracture and (2) non-linear flow in reservoir matrix would affect well productivity and fluid flow in the reservoir. Compared with our research before (Yue et al., 2020), here we extended this study into the development of multi-stage fractured horizontal wells (MFHWs) with large-scale complicated fracture geometry. The integrated workflow is based on the finite element method and consists of simulation models for proppant-laden fluid flow, fracture flow, and non-linear seepage flow, respectively. Simulation results indicate that the distribution of proppant inside the induced cracks significantly affects the productivity of the MFHW. When we assign an idealized proppant distribution instead of the real distribution, there will be an overestimation of 44.98% in daily oil rate and 30.63% in cumulative oil production after continuous development of 1000 days. Besides, threshold pressure gradient (TPG) also significantly affects the well performance in tight oil reservoirs. If we simply apply linear Darcy’s law to the reservoir matrix, the overall cumulative oil production can be overrated by 77% after 1000 days of development. In general, this research provides new insights into the development of tight oil reservoirs with TPG and meanwhile reveals the significance of proppant distribution and non-linear fluid flow in the production scenario design.

A practical workflow to design inflow control devices in SAGD projects to increase production and lower fresh water usage

This paper discusses the significance of inflow control devices (ICDs) in steam-assisted gravity drainage (SAGD) operations and their impact on well performance in different reservoir heterogeneities and qualities. The study focuses on investigating the specifications of ICD design using a numerical flow simulation model and flow rate versus pressure data obtained from a flow-loop experiment. The key advantage of employing flow-loop experiment data in the simulation would be a physics-based mechanistic model rather than using empirical correlations.The research collects core analysis data from three wells and particle size distribution (PSD) data from four wells in the same location. Permeability estimation is conducted for each PSD using a previously developed correlation. These data and other real data are used to construct the reservoir model, and the performance of liner deployed (LD) ICDs is compared by assigning flow-loop data to the simulation.By employing a relatively conservative production approach with subcooling between 10 °C and 15 °C, the cases with LDICDs demonstrate higher oil production rates, improved steam conformance, and lower cumulative steam oil ratios (cSOR) compared to the case without LDICDs. However, in a relatively challenging production scenario with subcooling between 1 °C and 5 °C, the case without ICDs cannot be simulated at the desired subcooling temperature and the cases with LDICDs improved the well productivity. LDICD#1 is identified in both scenarios as the best case due to its enhanced steam conformance and higher oil production rate.Compared to the case without ICDs, using LDICD#1 at higher subcooling temperatures leads to a 17 % increase in oil production rate, while reducing cSOR and natural gas usage by 8 % and 10 % respectively. Similarly, at lower subcooling temperatures, the case with LDICD#1 shows a 21 % increase in oil production rate and reductions of 12 % and 17 % in cSOR and consumed natural gas respectively, compared to the case without ICDs.The findings highlight the effectiveness of LDICDs at various subcooling levels and their potential application in SAGD projects to reduce freshwater usage and greenhouse gas emissions. Completion and production engineers can benefit from a better understanding of relative production performance to develop more effective operational designs.

Geomechanical modeling of ultradeep fault‐controlled carbonate reservoirs and its application, a case of the Fuman Oilfield in Tarim Basin

AbstractTo improve the development efficiency of ultradeep fault‐controlled carbonate reservoirs, the deformation and connectivity mechanism of fractures was revealed through large‐scale rock mechanical experiments. The in situ stress field and fracture activity distribution law of fault‐control carbonate reservoirs were clarified through geomechanical modeling. It is revealed that the fracture activity in different directions and the connectivity of the fracture and cavity in different parts are significantly different, the development effect of different well trajectories is analyzed, and the integrated working method of geological engineering is proposed to scientifically guide the well trajectory design and water injection scheme optimization. The results show that: (1) Large‐scale fractures and high‐angle fracture systems in the deformation of strike–slip faults are the key factors affecting reservoir quality. High‐pressure water injection can activate preexisting fractures, and it can extend on the basis of preexisting fractures, and even generate new fractures, which promote the interconnection of fault‐controlled fracture‐cave bodies in the vertical and horizontal directions. (2) During the process of high‐pressure water injection, the coupling change between mechanics and flow occurs inside the fracture body, the seepage environment is improved, and the oil and gas recovery factor is improved through cyclic lifting. (3) According to the shape and occurrence of the fault body and the dynamic shear deformation connectivity of the fault surface, the best well point and well trajectory of the directional well can be optimized, and the water injection scheme can be optimized. (4) The single‐well production increased by 1.45 × 104 t through high‐pressure water injection, the cumulative oil increase of the same fracture‐cavity body increased by 4.63 × 104 t. This method is highly efficient for ultradeep fault‐controlled oil reservoirs. The development provides a good theoretical basis and technical support, and plays a leading and exemplary role.

Multi-objective optimization of WAG injection using machine learning and data-driven Proxy models

In complex optimization processes such as CO2-water alternating gas (CO2-WAG), several iterative steps are needed before finding an optimal or sub-optimal set of solutions. This leads to time-consuming operations, especially when the simulation is run with a compositional simulator. Proxy models have been used to tackle this issue as they can replicate efficiently and accurately reservoir simulators in specific studies. However, the construction of such a proxy model, its basic database in particular, differs according to the designer and the objective function(s).In this study, a hybrid algorithm was designed that combined Artificial Neural Networks (ANN) and NSGA-II to find optimum solutions for a CO2-WAG injection process. The proxy model was developed based on a specific sampling method that considered the total injection time of a WAG cycle equal to one year and characterized by a new parameter, gas water injection time ratio (GWITR). The Latin Hypercube Design (LHD) is used to sample the inputs (bottom-hole flowing pressure of the producers, and water and gas injection rates) and the outputs are the cumulative oil recovery factor (FOE) and Net Present Value (NPV). After the proxy model was assessed, it was combined with Non-dominated Sorting Genetic Algorithm II (NSGA-II) to find the Pareto Front of the optimum solutions.The developed ANN model was able to predict the two outputs simultaneously with an R2 higher than 0.999 and an MSE of 6.5E-5. The found Pareto front, with good diversity and convergence, provided the operator with various solutions for decision-making.

Development Adjustment Scheme of a Low-Permeability Reservoir in the SN Oilfield

Due to the complexity of low-permeability reservoirs, there is no set of established plans to adjust the development of specific low-permeability reservoirs, and the final development adjustment plan should be determined through comprehensive consideration of many aspects. At present, the development of low-permeability reservoirs in the SN oilfield faces problems. It is urgent to formulate corresponding development adjustment plans to improve the current development situation. In view of the problems of the current development surface of low-permeability reservoirs in the SN oilfield, this paper used the previous research results of a low-permeability reservoir development adjustment for reference, evaluated the reservoir development effect, analyzed the remaining oil distribution via numerical reservoir simulation, and finally designed and optimized a development adjustment plan. The research results show that the injection–production ratio and pressure of low-permeability reservoirs in the SN oilfield were generally maintained, the oil production decreased, the water cut increased, and the remaining recoverable reserves were considerable; the historical matching quality of a reservoir numerical simulation was good. There was more remaining oil in the northeast of the J007 well block and the north of the J008 well block, and the potential of the L2 and L3 layers was great. The remaining oil was mainly concentrated in the areas with high positions, poor physical properties, and imperfect well patterns; the predicted cumulative oil production of Scheme IV in 15 years and recovery were the highest, with the best development effect and the highest economic benefit. This was determined as the development adjustment plan for low-permeability reservoirs in the SN oilfield. The research results of this paper aim to improve oil production, the ultimate recovery factor, and economic benefits of low-permeability reservoirs in the SN oilfield, and to provide a reference for the development of similar oilfields.

Intelligent Optimization of Gas Flooding Based on Multi-Objective Approach for Efficient Reservoir Management

The efficient development of oil reservoirs mainly depends on the comprehensive optimization of the subsurface fluid flow process. As an intelligent analysis technique, artificial intelligence provides a novel solution to multi-objective optimization (MOO) problems. In this study, an intelligent agent model based on the Transformer framework with the assistance of the multi-objective particle swarm optimization (MOPSO) algorithm has been utilized to optimize the gas flooding injection–production parameters in a well pattern in the Middle East. Firstly, 10 types of surveillance data covering 12 years from the target reservoir were gathered to provide a data foundation for model training and analysis. The prediction performance of the Transformer model reflected its higher accuracy compared to traditional reservoir numerical simulation (RNS) and other intelligent methods. The production prediction results based on the Transformer model were 21, 12, and 4 percentage points higher than those of RNS, bagging, and the bi-directional gated recurrent unit (Bi-GRU) in terms of accuracy, and it showed similar trends in the gas–oil ratio (GOR) prediction results. Secondly, the Pareto-based MOPSO algorithm was utilized to fulfil the two contradictory objectives of maximizing oil production and minimizing GOR simultaneously. After 10,000 iterations, the optimal injection–production parameters were proposed based on the generated Pareto frontier. To validate the feasibility and superiority of the developed approach, the development effects of three injection–production schemes were predicted in the intelligent agent model. In the next 400 days of production, the cumulative oil production increased by 25.3% compared to the average distribution method and 12.7% compared to the reservoir engineering method, while GOR was reduced by 27.1% and 15.3%, respectively. The results show that MOPSO results in a strategy that more appropriately optimizes oil production and GOR compared to some previous efforts published in the literature. The injection–production parameter optimization method based on the intelligent agent model and MOPSO algorithm can help decision makers to update the conservative development strategy and improve the development effect.

A new method for the characterization of microcracks based on seepage characteristics

Microcracks are the main seepage channels and reservoir space for oil and gas in dense sandstone reservoirs, and the degree of development dominates the reservoir’s high and stable production capacity. A new method has been devised to address the lack of quantitative identification and characterization methods for microcrack networks. The method is based on core stress sensitivity, permeability anisotropy, and two-phase seepage rule testing. By improving upon the traditional black oil model, this method can accurately calculate the impact that microcracks of varying degrees of development have on the capacity of tight oil reservoirs. The study shows that 1) the higher the degree of microcrack development, the stronger the reservoir stress sensitivity and the greater the permeability anisotropy. As the degree of microcrack development increases, the irreducible water saturation decreases, the residual oil saturation gradually increases, and the oil–water two-phase co-infiltration zone becomes more extensive and smaller. The degree of microcrack development in tight reservoirs can be characterized based on the seepage characteristic parameters; 2) a microcrack characterization method and classification criteria have been established. It is based on stress sensitivity coefficients, permeability anisotropy parameters, and phase seepage characteristics in cores with different microcrack development degrees. For the first time, the method enables a macroscopic-level description of microcrack seepage; 3) numerical calculations show that the degree of microcrack development significantly affects the reservoir’s oil production and water production. The higher the degree of microcrack development, the higher the reservoir’s initial oil production and cumulative oil production. However, when the degree of microcrack development is too high, the microcracks are connected, thus exhibiting the nature of large fractures. This strengthens the bypassing communication effect and causes the microscopic inhomogeneity to strengthen, the oil production decreases rapidly, and water production increases quickly at the later stage. This research result enriches the reservoir microcrack characterization and evaluation system, which has essential theoretical guidance and practical significance for the rational and effective development of tight oil and tight sandstone gas.

Investigation of the Oil-Soluble Particulate Temporary Plugging Agent-Assisted Water Huff ‘n’ Puff Enhanced Oil Recovery in Tight Oil Reservoirs

Summary Water huff ‘n’ puff is an effective enhanced oil recovery (EOR) technology for tight oil reservoirs. However, the oil production of horizontal wells declines seriously after several huff ‘n’ puff cycles, and a large amount of oil is still trapped in the reservoir due to the heterogeneity of fracturing sections. The temporary plugging agent had been used for plugging high-permeability areas and thus diverting the following fluid into small permeability areas. It would improve the sweep efficiency of flooding fluid, enhancing oil recovery. However, the use of the oil-soluble particulate temporary plugging agent in the water huff ‘n’ puff application is barely reported. Therefore, the feasibility and influencing factors of oil-soluble particulate temporary plugging agent-assisted water huff ‘n’ puff (TAWHP) in enhancing oil recovery was investigated in this study. First, based on the evaluation of the performance of the oil-soluble particulate temporary plugging agent, the oil recovery of fractured core samples with different apertures for water huff ‘n’ puff and TAWHP was compared via the parallel-core experiment to verify the feasibility of TAWHP in enhancing oil recovery. The temporary plugging agent had good oil solubility, a low residual rate in the formation, and little damage to the formation. The oil recovery yielded by TAWHP was 5.17% higher than the traditional water huff ‘n’ puff process. More oil (i.e., about 1.71%) could be expelled from the fractured core samples with a small aperture. It indicated that the EOR performance yielded by water huff ‘n’ puff after several cycles could be enhanced by adding the oil-soluble particulate temporary plugging agent. After that, a mathematical model of TAWHP was established to investigate the effect of TAWHP parameters on EOR performance. The simulation results showed that the cumulative oil production increased with the increase in injection time of the temporary plugging agent solution, but the trend would level-off after 10 minutes. Moreover, as the diversion index increased, the effect of the injection rate on cumulative oil production gradually enhanced while the effect of the soaking time gradually weakened. Furthermore, the difference in cumulative oil production at different diversion indexes gradually increased as the huff ‘n’ puff cycle increased. This work could provide theoretical guidance for water huff ‘n’ puff enhancing oil recovery after several cycles.

General Optimization Framework of Water Huff-n-Puff Based on Embedded Discrete Fracture Model Technology in Fractured Tight Oil Reservoir: A Case Study of Mazhong Reservoir in the Santanghu Basin in China

Summary Water injection huff-n-puff (WHnP) is currently an important technology to improve the recovery of tight reservoirs. On the one hand, this technology can replenish the formation energy, and on the other hand, it can effectively replace the oil in a tight reservoir. In this paper, the effect of WHnP on cumulative oil production and oil increase rate is simulated and analyzed by comparing depleted development and WHnP scenarios, using numerical simulation methods. A field-scale numerical simulation was modeled based on typical fluid, reservoir, and fracture characteristics of Mazhong tight oil, coupled with geomechanical effects, stress sensitivity, and embedded discrete fractures. The result of different WHnP cycles is studied, and the limiting WHnP cycle is determined to be four cycles. The WHnP efficiency is compared for different permeability scales from 0.005 to 1 md, and it is determined that WHnP at a permeability of 0.01 md resulted in the largest production enhancement. Subsequently, sensitivity studies are conducted using an orthogonal experimental design for six uncertain parameters, including the WHnP cycle, production pressure difference, permeability, natural fracture density, hydraulic fracture half-length, and conductivity. The results show that throughput period and permeability are important parameters affecting cumulative oil production, and permeability and natural fracture density are important parameters affecting oil increase rate. In addition, contour plots of permeability and WHnP cycle, hydraulic fracture half-length, and conductivity are generated. Based on these plots, the optimal conditions with better enhanced recovery results in different WHnP scenarios can be easily determined. This study can better solve the problems encountered in WHnP of tight reservoirs and provide a theoretical basis for stable and efficient development.

Study and Application of Oily Sludge Profile Control Technology in Heavy Oil Reservoir

In the process of steam injection development of heavy oil, due to the serious heterogeneity and interference of steam channeling in the high-permeability layer, there is a lot of oily sludge in the produced liquid of oil wells, which is difficult to deal with. According to existing profile control technology and the related properties of oily sludge, a profile control system was developed by using oily sludge as the main agent and by adding other additives. At the same time, the properties of sludge, the matching relationship between the particle size of sludge and the formation of pore roar, the temperature resistance, the plugging ability, and other contents were studied. The agent featured an adjustable curing time (3 to 300 h) and resistance to pressures greater than 6 MPa and temperatures greater than 350 °C. After the agent was injected into the high-permeability steam channeling, the system was cemented with the formation rock and the sealing rate was more than 85%, without any damage to the low- and medium-permeability layers. According to the different characteristics of the production well and steam injection well, the construction technology was optimized, the oily sludge profile control technology suitable for heavy oil reservoirs was formed, and the field test was carried out. At present, more than 150 wells have been used in the field, with a cumulative oil increase of 10,756 tons. The technology not only solves the environmental pollution caused by oily sludge but also reduces the cost of thermal recovery of heavy oil, with great significance for improving the final recovery efficiency and commercial benefits of the oilfield.

Nanocomposite of binary colloids in effective CO2 utilization in porous media for enhanced oil production and wettability alteration

Carbon dioxide injection is a renowned enhanced oil recovery method, where the inclusion of a novel material is appreciated via mobility control of injected CO2 during flow through porous and permeable oil reservoirs. Therefore, the combination of nanoparticles and their associated additives is recommended for foam flooding schemes. Thus, this study reports the use of nanocomposites of SiO2 (0.1 – 2 wt%) and TiO2 (0.1 wt%) in promoting CO2 utilization in oil recovery projects. The assessment of a foam emulsion is a crucial and interesting task to understand the basic fundamental of three-phase interactions viz., Crude oil (oil phase), nanocomposites (aqueous phase), and CO2 (gas phase) in the context of foam-emulsion, and was examined via microscopic and rheological characterization. CO2 foam showed temperature tolerance capability and a shear-thinning viscoelastic nature due to the inclusion of nanocomposites. Furthermore, wettability alteration was understood via contact angle measurements between CO2 and nanocomposite. Interestingly, the contact angle was reduced to 39° after the inclusion of 0.1 wt% TiO2 and CO2 in the system. Finally, nanocomposite stabilized CO2 foam demonstrated a total cumulative oil recovery of 78 % at (40 °C), higher than the cumulative oil recovery (70 %) associated with nanocomposite without CO2. The results of this study suggest that CO2 utilization for oil recovery can be enhanced by developing its viscous foam, stabilized by a nanocomposite of SiO2 and TiO2 nanoparticles.

CO2 huff-n-puff combined with radial borehole fracturing to enhance oil recovery and store CO2 in a shale oil reservoir

This study pioneers the integration of CO2 huff-n-puff and radial borehole fracturing, enhancing shale oil recovery and facilitating CO2 storage. To evaluate the performance of CO2 huff-n-puff with radial borehole fracturing, a numerical compositional model is developed, enabling a comparison of CO2 huff-n-puff performance between radial borehole and horizontal well fracturing, while assessing the influence of various parameters, including CO2 diffusion, lateral configuration, fracture parameters, cycle number, soak duration, production time, injection pressure, and production pressure on oil and gas production, as well as CO2 storage. The results indicate that increasing the number of layers in radial borehole construction can effectively enhance the vertical exploitation efficiency of oil reservoirs. The cumulative oil production of the three-layer, four-branch radial borehole fracturing pattern is 1.66 times higher than that of the horizontal fracturing with 20 fractures. Moreover, it also identifies the principle of enhancing the number of radial boreholes per layer and increasing fracture length to optimize horizontal reservoir exploitation. A 5% reduction in individual cyclic duration from the base case significantly influences the initial high-flow phase, yielding a hydrocarbon production 1.35 times higher. Further strategies to enhance CO2 huff-n-puff efficacy include diminishing the soak stage's proportion and adjusting the temporal proportion of the production stage to 75% for oil extraction and 30% for CO2 storage. Increasing the injection pressure impacts the storage capacity of CO2 significantly, whereas reducing production pressure affects oil and gas production. The findings of this study present a novel method and provide a theoretical foundation for the efficient and economical development of shale oil.

Experimental study on the mechanism of five point pattern refracturing for vertical & horizontal wells in low permeability and tight oil reservoirs

Low permeability oil reservoir has the characteristics of low porosity and low permeability. The initial fracturing can effectively improve the recovery of the reservoir, but the physical mechanism of refracturing to improve the recovery is still lack of systematic research. In this paper, the refracturing effect of low permeability reservoirs under the condition of five point well pattern is clarified; the refracturing mechanism of vertical-horizontal well combination is revealed; the reservoir production performance characteristics under different soak time conditions are analyzed. It is found that: (a) after 1st fracturing, the area between the two fractures still has a high residual oil, which is the material basis for refracturing. (b) After refracturing, there are secondary fractures connecting the main fractures. The crude oil in the low permeability reservoir can flow not only to the main fracture and horizontal wellbore, but also to the secondary fractures. This leads to the effective reduction of oil saturation between the main fractures. (c) The influence of soak time on cumulative oil production is obvious. With the increase of soak time, the cumulative oil production increases significantly.

Enrichment factors of movable hydrocarbons in lacustrine shale oil and exploration potential of shale oil in Gulong Sag, Songliao Basin, NE China

The geological characteristics and production practices of the major middle- and high-maturity shale oil exploration areas in China are analyzed. Combined with laboratory results, it is clear that three essential conditions, i.e. economic initial production, commercial cumulative oil production of single well, and large-scale recoverable reserves confirmed by the testing production, determine whether the continental shale oil can be put into large-scale commercial development. The quantity and quality of movable hydrocarbons are confirmed to be crucial to economic development of shale oil, and focuses in evaluation of shale oil enrichment area/interval. The evaluation indexes of movable hydrocarbon enrichment include: (1) the material basis for forming retained hydrocarbon, including TOC>2% (preferentially 3%–4%), and type I–II1 kerogens; (2) the mobility of retained hydrocarbon, which is closely related to the hydrocarbon composition and flow behaviors of light/heavy components, and can be evaluated from the perspectives of thermal maturity (Ro), gas-oil ratio (GOR), crude oil density, quality of hydrocarbon components, preservation conditions; and (3) the reservoir characteristics associated with the engineering reconstruction, including the main pore throat distribution zone, reservoir physical properties (including fractures), lamellation feature and diagenetic stage, etc. Accordingly, 13 evaluation indexes in three categories and their reference values are established. The evaluation indicates that the light shale oil zones in the Gulong Sag of Songliao Basin have the most favorable enrichment conditions of movable hydrocarbons, followed by light oil and black oil zones, containing 20.8×108 t light oil resources in reservoirs with Ro>1.2%, pressure coefficient greater than 1.4, effective porosity greater than 6%, crude oil density less than 0.82 g/cm3, and GOR>100 m3/m3. The shale oil in the Gulong Sag can be explored and developed separately by the categories (resource sweet spot, engineering sweet spot, and tight oil sweet spot) depending on shale oil flowability. The Gulong Sag is the most promising area to achieve large-scale breakthrough and production of continental shale oil in China.