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Conventional numerical solutions and empirical formulae for predicting the initial productivity of oil wells in low-permeability reservoirs are limited to specific reservoirs and relatively simple scenarios. Moreover, the few influencing factors are less considered and the application model is more ideal. A productivity prediction method based on machine learning algorithms is established to improve the lack of application performance and incomplete coverage of traditional mathematical modelling for productivity prediction. A comprehensive analysis was conducted on the JY extra-low-permeability oilfield, considering its geological structure and various factors that may impact its extraction and production. The study collected 13 factors that influence the initial productivity of 181 wells. The Spearman correlation coefficient, ReliefF feature selection algorithm, and random forest selection algorithm were used in combination to rank the importance of these factors. The screening of seven main controlling factors was completed. The particle swarm optimization–extreme learning machine algorithm was adopted to construct the initial-productivity model. The primary control factors and the known initial productivity of 127 wells were used to train the model, which was then used to verify the initial productivity of the remaining 54 wells. In the particle swarm optimization–extreme learning machine (PSO-ELM) algorithm model, the root-mean-square error (RMSE) is 0.035 and the correlation factor (R2) is 0.905. Therefore, the PSO-ELM algorithm has a high accuracy and a fast computing speed in predicting the initial productivity. This approach will provide new insights into the development of initial-productivity predictions and contribute to the efficient production of low-permeability reservoirs.

The phase behavior of fluid is essential for predicting ultimate oil recovery and determining optimal production parameters. The pore size in shale porous media is nanopore, which causes different phase behaviors of fluid in unconventional reservoirs. Nanopores in shale media can be regard as semipermeable membrane to filter heavy components (sieving effect) in shale oil, which leads to the different distributions of fluid components and different phase behaviors. In addition, the phase behavior of fluid in nanopores can be significantly altered by large capillary pressure. In this paper, the phase behavior of fluid in shale reservoirs is investigated by a new two-phase flash algorithm considering sieving effect and capillary pressure. Firstly, membrane efficiency and capillary pressure are introduced to establish a thermodynamic equilibrium model that is solved by Rachford–Rice flash calculation and Newton–Raphson method. The capillary pressures in different pore sizes are calculated by the Young–Laplace equation. Then, the influences of sieving effect and capillary pressure on phase behavior are analyzed. The results indicate that capillary pressure can suppress the bubble point pressure of fluid in nanopores. The distributions of fluid components are different in various parts of shale media. In the unfiltered part, density and viscosity of fluid are higher. Finally, it is found that the membrane efficiency can be improved by CO2 injection. The minimum miscibility pressure for shale oil–CO2 system is also studied. The developed model provides a better understanding of the phase behavior of fluid in shale oil reservoirs.

Recently, special attention has been drawn to the high-salt argillaceous dolomite reservoir in Jianghan basin, China due to its abundant oil resources with complex geological conditions. However, the current production methods used to develop this reservoir are not efficient with low throughput. Hence, the purpose of this paper is to explore the main possible reasons affecting the oil well productivity and determine suitable field development method for the target oilfield through experimental and numerical simulation approaches. The mercury injection capillary pressure (MICP) test results indicate that the average pore radius of samples is 0.0144 μm, and pore size distribution (PSD) results from MICP indicate that single peaks appeared in the PSD curves of the pore type samples. Permeability peaks of the samples range from 0.01 to 0.03 μm, and mesopores make most of the permeability contribution of the samples, which also reveals the low-permeability and porosity characteristics of the target oilfield. The results of core stress sensitivity tests show that the largest permeability damage rate is 98.97% with an average permeability damage rate of 98.37% while the maximum porosity damage rate is less than 10% with an average damage rate of 5.57% during the process of depressurization. The results of Non-Darcy percolation experiment indicate that threshold pressure gradient testing by water is about 0.03 MPa/m, which is close to the actual situation of the target oilfield. Numerical simulation method that considers the impact of threshold pressure gradient and stress sensitivity were established to study flooding patterns deployment for the research area. The simulation results show that performing water alternating gas flooding (WAG) by using CO2 is recommended for the development of the high-salt reservoir with inverse five-spot flooding pattern made up of 400 m well spacing in X-direction and 150 m row spacing.

CO2 flooding recovery strongly depends on the minimum miscibility pressure (MMP). Conventional tests to determine gas–oil MMP such as rising bubble apparatus and slim tube displacement are either costly or time consuming. In order to propose a quick and accurate model to determine MMP, a back-propagation neural network is presented for MMP prediction during pure and impure CO2 injections. Five new variables were screened as input parameters to the network. Next, the network was optimized using five evolutionary algorithms, and this work highlights that three of these evolutionary algorithms (e.g. Mind Evolutionary, Artificial Bee Colony, and Dragonfly) are firstly used to predict MMP. Then, data from the literature were input to the optimized network to train it. Statistical evaluation and graphical analyses were used to evaluate the performance of the proposed models and for comparison with published MMP correlates to obtain the optimal model for predicting MMP. The back-propagation model optimized using the dragonfly algorithm exhibited the highest accuracy among all those considered and MMP correlates; its coefficient of determination, average absolute percent relative error, root mean square error, and standard deviation were 0.965, 5.79%, 206.1, and 0.08, respectively. In addition, reservoir temperature was determined as the strongest MMP predictor (Pearson correlation = 0.63) based on sensitivity analysis.

During the past years, the recovery of unconventional gas formation has attracted lots of attention and achieved huge success. To produce gas from the low-permeable unconventional formations, hydraulic fracturing technology is essential and critical. In this paper, we present the development of a three-dimensional thermal-hydraulic-mechanical numerical simulator for the simulation of hydraulic fracturing operations in tight sandstone reservoirs. Our simulator is based on integrated finite difference (IFD) method, In this method, the simulation domain is subdivided into sub domains and the governing equations are integrated over a sub domain with flux terms expressed as an integral over the sub domain boundary using the divergence theorem. Our simulator conducts coupled thermal-hydraulic-mechanical simulation of the initiation and extension of hydraulic fractures. It also calculates the mass/heat transport of injected hydraulic fluids as well as proppants. Our simulator is able to handle anisotropic formations with multiple layers. Our simulator has been validated by comparing with an analytical solution as well as Ribeiro and Sharma model. Our model can simulate fracture spacing effect on fracture profile when combining IFD with Discontinuous Displacement Method (DDM).

The dispersion of silica dioxide (SiO2)/sodium lauryl sulfate (SDS) have been widely used in the oilfield development and the remaining oil displacement, but its instability is still a problem in the practical engineering application. In this paper, the mechanism of foam stability was investigated by combining the measurement of interfacial energy of nanoparticles at the gas-liquid interface with the dynamics simulation of molecular diffusion. The results showed that the addition of SiO2 nanoparticles improved the interfacial energy and interfacial activity at the gas-liquid interface, meanwhile limited the movement of SDS molecules and water molecules, which was beneficial for the foam stability. Notably, the addition of modified SiO2 nanoparticles further enhanced the interfacial energy at the gas-liquid interface and strengthened the restriction of water/SDS molecular movement, thereby slowing down the drainage and decay of the foam dispersions. The mechanism investigation was of benefit for foam flooding engineering application.

It is of great significance to understand the dynamic mechanism of dispersed non-aqueous gas bubbles in a porous media to develop hydrocarbon reservoirs for enhanced oil recovery (EOR). In this work, series of experiments about bubbles rising motion behavior in different influence factors were conducted through video photography enhanced with image analysis. The results showed that with the increase of the bubble length and the glass beads size, the average velocity of bubbles ascended first and then tended to be stable, which was mainly controlled by the buoyancy and the drag resistance force. On the contrary, the average velocity decreased with the pore-throat ratio increasing for bubbles with 20 mm length, which resulted from the decrease of buoyancy and the increment of drag force and interface tension due to the more liquid-gas contact area in the pores and throats occupied by the bubble. The bubbles average velocity showed the same trend with the increase of inclination angles and liquid viscosities, and the maximum average velocities were 50°–60° of inclination angle and 40%–50% of mass fraction, respectively.

Low-velocity non-Darcy flow often occurs in low permeability reservoirs. In this paper, we discuss how to incorporate a non-Darcy flow correction into embedded discrete fracture modeling (EDFM). The resulting method is validated by reproducing type curves containing the characteristic no-flow segment, followed by a nonlinear and a linear segment. Simulation results are also validated against a direct simulation method that uses local grid refinement to (almost) resolve hydraulic fractures. Second, we discuss how grid-based flow diagnostics can be formulated on top of the new EDFM method and used to provide computationally inexpensive predictions of flow patterns, interwell connections, and measures of dynamic heterogeneity. We then demonstrate how such flow diagnostics can be used to optimize well placement and improve oil recovery.

The most widely used production decline forecasting tools are numerical reservoir simulation, material balance estimates and advanced methods of production decline analysis. Besides, these existing production decline evaluation techniques for unconventional reserves estimations have underlying limitations and assumptions incorporated into their formulation which can result into under- and overestimation. This further raises the debate about which decline curve analysis (DCA) is better than the other for unconventional reservoirs predictions. Currently, data-driven artificial neural network (ANN) has emerged as a new paradigm capable of mapping complex functional relationships. In this present study, ANN technology was used to calibrate tight gas carbonate field historical declining trends which exhibit high early peak production rate and quick decline. Hereafter, making reliable predictions posed as a challenge for the complex target field and hard computing protocols. Therefore, this research applied and tested the capability of backpropagation artificial neural network (BPANN), radial basis function neural network (RBNN) and generalized regression neural network (GRNN) as DCA techniques for predicting the historical production decline trends of an ultra-low porosity and permeability tight gas reservoir. The optimum trained ANN DCA models developed were validated with another surrounding well’s dataset, producing acceptable results in agreement with the actual field data. The GRNN DCA model’s testing performance was poor, and its smoothing parameter was optimized with particle swarm optimization (PSO) algorithm which gave satisfactory results comparable to standalone BPANN and RBFNN DCA models. Furthermore, the optimum ANN DCA models’ generalization strength across the entire field dataset revealed that the developed models’ predictions were robust as compared to the data-driven Arps hyperbolic and power law exponential DCA models. This was evident from the statistical performance criteria employed which indicated that BPANN, RBFNN and PSO-GRNN DCA models are plausible better fit models for matching the target field’s historical decline performances. Also, a novel non-Darcy flow horizontal well productivity evaluation model for the target field was developed based on stress sensitivity coefficient (SSC) of permeability, tortuosity factor, Klinkenberg effect, near-wellbore turbulence effect and threshold pressure gradient (TPG) for validating the ANN DCA models predictions. The productivity model was validated with published horizontal well model with closely matched results. For inflow performances, the horizontal well model with turbulence minimizes negative effects on non-Darcy flow rates than without turbulence. Additionally, pressure drawdown influences the tight gas well productivity such that the lower the pressure drawdown, the smaller the tight gas well productivity. The operating points of the tight gas well were determined through inflow performance relation and tubing performance relation at different SSC and TPG for $$ 3{\raise0.5ex\hbox{$\scriptstyle 1$} \kern-0.1em/\kern-0.15em \lower0.25ex\hbox{$\scriptstyle 2$}} $$ in tubing size. In another case, synthetic unconventional simulation data with long production history were used for future forecast of 5, 24 and 70 months of production rate and cumulative production which gave pretty close results for all the DCA models, unlike the real field datasets, where the empirical rate-time models under and overestimate. In all, these ANN DCA models and the horizontal well productivity model derived will serve as new computational tools for complementing existing DCA techniques for better understanding of unconventional reservoirs’ production decline performance.

This paper proposes stochastic petroleum porous media modeling for immiscible fluid flow simulation using Dykstra–Parson coefficient (VDP) and autocorrelation lengths to generate 2D stochastic permeability values which were also used to generate porosity fields through a linear interpolation technique based on Carman–Kozeny equation. The proposed method of permeability field generation in this study was compared to turning bands method (TBM) and uniform sampling randomization method (USRM). On the other hand, many studies have also reported that, upstream mobility weighting schemes, commonly used in conventional numerical reservoir simulators do not accurately capture immiscible displacement shocks and discontinuities through stochastically generated porous media. This can be attributed to high level of numerical smearing in first-order schemes, oftentimes misinterpreted as subsurface geological features. Therefore, this work employs high-resolution schemes of SUPERBEE flux limiter, weighted essentially non-oscillatory scheme (WENO), and monotone upstream-centered schemes for conservation laws (MUSCL) to accurately capture immiscible fluid flow transport in stochastic porous media. The high-order schemes results match well with Buckley Leverett (BL) analytical solution without any non-oscillatory solutions. The governing fluid flow equations were solved numerically using simultaneous solution (SS) technique, sequential solution (SEQ) technique and iterative implicit pressure and explicit saturation (IMPES) technique which produce acceptable numerical stability and convergence rate. A comparative and numerical examples study of flow transport through the proposed method, TBM and USRM permeability fields revealed detailed subsurface instabilities with their corresponding ultimate recovery factors. Also, the impact of autocorrelation lengths on immiscible fluid flow transport were analyzed and quantified. A finite number of lines used in the TBM resulted into visual artifact banding phenomenon unlike the proposed method and USRM. In all, the proposed permeability and porosity fields generation coupled with the numerical simulator developed will aid in developing efficient mobility control schemes to improve on poor volumetric sweep efficiency in porous media.

Modeling viscous fingering perturbations in stochastic fields have always been a formidable task for geoscientists. Although fingering and channeling are often used synonymously to describe uneven front displacements, in fact, both phenomena represent different bypassing effects on hydrocarbon ultimate recovery. However, fingering perturbations in stochastic fields to invoke them during simulation often lead to severe channeling. Hence, the focus of this paper is to develop a finite volume numerical simulator with a level of certainty where fingering perturbations in stochastic fields do not result into severe channeling. The simulator development involves discretization of convection–diffusion and pressure equations with total variation diminishing and central differencing schemes, respectively. Correlated stochastic fields for simulation runs were created using convolution with a Gaussian filter achieved through 2D fast and inverse Fourier transform, Dykstra–Parsons coefficient, random porosity generator, and autocorrelation lengths. The obtained pressure and tracer concentration profiles were solved by iterative implicit pressure and explicit concentration approach, respectively. Numerical results of concentration profiles indicated that, unlike flow channeling, viscous fingering occurred in both homogeneous and heterogeneous fields. The obtained flow pattern map captures these flow regimes, namely fluid mobility fingering, channeling, and heterogeneous fingering. Sensitivity analyses of diffusion coefficient contributions to channeling and fingering phenomena are of extreme importance. The simulator shows a good validation with analytical solution while insensitive to grid refinements and spurious oscillations. The simulator is an improvement on first-order scheme simulators with the capability of computationally tracking fingering perturbations in stochastic fields which often result into channeling anomalies.

In consideration of the limited adaptability scope, low accuracy and high demand of great cost data of existent fracture prediction methods, a new fracture predicting method was advanced by implementing geological static data and production dynamic data from the Triassic Chang 63 reservoirs in the Huaqing Oilfield. Five constraints, lithology, sedimentary facies, thickness, rock rupture index and fracture intensity controlling the development of fractures were sorted out based on the static geological data. The multiple linear regression method was adopted to work out the quantitative relationships between the five constraints and fracture density, and the fracture density property of the whole area was calculated. Based on production dynamic data of well history, tracer, well interference test and intake profile test, the direction and distribution of fracture horizontally and vertically were figured out by reservoir engineering analysis method. The fracture density property was verified and quantitatively corrected with numerical simulation, and a 3D discrete fracture geological model in agreement with both geological cognition and dynamic production performance was built. The numerical simulation shows that the fracture model has higher fitting consistency, high reliability and adaptability. Key words: fractured oil reservoir, natural fracture, fracture geological model, fracture prediction, Huaqing Oilfield, Ordos Basin

To enhance oil recovery and optimize a production plan, injected water or gas fluid should be monitored and tracked, which can be realized by gas tracer technology. Tracer test technology has become an effective method for evaluating the flow condition of reservoirs and estimate reservoir properties. Gas tracers, such as chemical and radioactive materials, have been used to identify well-to-well connectivity, reservoir heterogeneity, high-permeability pay zones, sweep efficiency, and residual oil saturation. Moreover, tracer tests have been used to evaluate well interference among multiple hydraulically fractured wells and qualitatively predict possible fracture geometries. Therefore, the accurate quantification of tracer transport is of great importance. However, theoretical study of gas tracers in a condensate gas reservoir has not been thoroughly conducted to date. Current tracer transport models mostly focus on the gas tracer flow in oil reservoirs and cannot be directly applied to condensate gas reservoirs. To the best of our knowledge, the application of a gas tracer to recycle gas injection in gas condensate reservoirs has not been thoroughly studied. In this paper, we propose a mathematical model to quantitatively describe the gas tracer transport mechanism in condensate gas reservoirs. Our mathematical model is based on the mass conservation law and is numerically solved via the Integral Finite Difference method. The results predicted by our model have been compared to and verified by real data collected from the field. The model has been used to optimize the recovery of the Yaha Condensate Gas Field in the Tarim Basin, China. With the assistance of our tracer transport model, the pressure drawdown speed of the Yaha field has been successfully slowed from 0.8 MPa/year to 0.5 MPa/year. Generally, this study not only provides key insights into the transport mechanism of gas tracers but also presents the application of numerical tools to guide the production of gas condensate reservoirs. The technique introduced in this study could be potentially extended to condensate oil production in other fields.

Water fingering phenomenon in an oil layer or water preferential injection into highly permeable layers in a multilayer reservoir often leads to a low sweep efficiency in a strong heterogeneous oil reservoir depending on water flooding for enhanced oil recovery (EOR). EOR by means of permeability control during water flooding periods in heterogeneous oil formations has been corroborated by previous experiments in the laboratory and field trial in mature oil fields. However, the quantitative relationships between EOR and permeability control in oil reservoirs are not clearly understood currently. In this paper, the mechanisms of permeability control in oil reservoirs were analyzed by theoretical approaches. Then, a three dimensional multi-phase flow mathematical model considering migration of solid permeability control agents (PCA) was presented. A numerical simulator for predicting multi-phase flow of permeability control in oil reservoirs was developed in Fortran codes. In addition, the permeability reduction and water-cut change induced by PCA calculated by the simulator are validated by experiments. Furthermore, a two and a three dimensional geological models with different types of permeability control agents injected into the highly permeable layer for EOR were studied by using the new simulator developed in this work. The simulation results demonstrate the permeability control processes with elapsed time as well as oil production performance influenced by permeability control. It also reveals a mechanism of permeability control for EOR, and suggests oil recovery improved by 4.9–8.8% in the 2D simulation and 6.1% in the 3D simulation example. It validates the feasibility of numerical simulation and importance of permeability control technology for EOR.

Based on the theory of non-Darcy seepage, a mathematical model for CO2 miscible and immiscible concurrent flooding considering changes of oil viscosity and threshold pressure gradient of oil and CO2 is established. A computational method of critical well spacing of CO2 miscible and immiscible concurrent flooding in ultra-low permeability reservoirs is deduced by solving the distribution of CO2 concentration in miscible flooding area with the mass transfer-diffusion-absorption equation and solving the saturation equation of immiscible affected area with characteristic line method. A critical well spacing example is built in the F142 and G89 reservoir blocks and the results show: (1) The critical well spacing increases with gas injection pressure, while decreases with gas injection speed; (2) The contribution of length in pure CO2 seepage area to the critical well spacing is the largest, the contribution of length in CO2-Oil effective mass transfer area and immiscible affected area is secondary, the contribution of pure oil area is the least, the gap of length between pure CO2 seepage area and CO2-Oil effective mass transfer area and immiscible affected area decreases with gas injection speed and it increases with the decreasing of gas injection speed, meanwhile, the law is more significant; (3) Pressure drop gradient of miscible affected area is significantly different from that of immiscible affected area and pressure drop gradient of CO2-Oil effective mass transfer area in miscible affected area is bigger than that of immiscible affected area. Key words: ultra-low permeability reservoirs, miscible flooding, immiscible flooding, critical well spacing, threshold pressure gradient

The fault block hydrocarbon reservoirs developed by water flooding in Shengli Oilfield have entered into the period of high water cut and low oil recovery. The residual oil to be recovered is challenging by using the unidirectional water or gas displacement method in producing oil from the reservoirs because of water invasion or gas channeling. A novel method of bidirectional displacement with artificial nitrogen gas cap and edge water is presented to improve the oilfield development recovery efficiency. This novel method refers to the nitrogen gas injection at the top of the inclined reservoir and the edge water injection at the bottom of the reservoir simultaneously. The experiments of the sandpack model are performed to explain the benefits of nitrogen gas flooding and to evaluate quantitatively the production performance of the bidirectional displacement process. A numerical simulation technique based on the proposed method is employed to find out befitting reservoirs for implementation of this new novel method. The X48 inclined fault block hydrocarbon reservoir in Dongxin production area, Shengli Oilfield, is selected as the actual research block to verify the benefits of bidirectional displacement with artificial nitrogen gas cap and edge water. The results indicate that the oil recovery by bidirectional displacement of nitrogen gas injection in the X4841 injection well and edge water injection in the X48CXN9 injection well cooperatively is higher than that of unidirectional water flooding or gas flooding in the X4841 injection well. The oil recovery factor increases by 11.2% than that by the original water injection development in the X48CXN9 injection well. Another interesting finding in this work was that, for the oil recovery, an appropriate ratio relationship is established between the nitrogen injection rate and the water injection rate regardless of production rate.

In China, many oilfields with low permeability and heterogeneity have entered the secondary oil recovery stage, in which more oil displacement agents for expanding sweep volume has become a key technology. A water-gas dispersion flooding system is reasonably proposed to change the seepage resistance and adjust the mobility ratio. In this EOR technique, the generation of micron-sized bubbles in the low-permeability reservoir is of considerable interest. In this study, a visual device by using an orifice spraying method was designed to simulate reservoir conditions with high temperature and high pressure, and efficiently to produce more microbubbles. Based on the orifice spraying method, the morphological characteristics of microbubbles generated by different orifice plate materials were compared, which provided the choice of the microbubbles generation by the orifice spraying method for laboratory experiments. Besides, the influence of different factors on the quantity and size of microbubbles produced by a single orifice plate was presented in detail. The experimental results showed that the diameter of the microbubbles generated by the orifice spraying method under a hypothetic reservoir condition was about 10–100 μm. These visual experimental devices were practically designed to meet the demand of the micron-level pores and throats to enhance oil recovery in low-permeability reservoirs. This investigation of microbubbles generation provided the basic research means for further preparation of a water-gas dispersion flooding system.

In tilted fault block reservoirs with edge water, the remaining oil is usually formed and located at the structurally highest. The gas and water bidirectional displacement process is an effective method to recover this type of remaining oil in these reservoirs. However, there is no optimizing method to design the injection-production schedule of this process for the maximum oil recovery. In this study, the imaging and superposition principle, Pollock method, equivalence principle, and Buckley-Leverett method were combined to develop a novel semi-analytical method for optimizing the injection-production schedule. An example study was carried out for verifying the proposed semi-analytical method and validated with the numerical simulation method. Furthermore, sensitive factors of this displacement process were quantitatively analyzed by the proposed method. The results showed that the optimized synergy of the gas and water can maximize the oil recovery for the bidirectional displacement process. Compared with no injection, inadequate injection, and excess injection of gas, the breakthrough recovery can be increased by 3.7%, 0.8%, and 4.88%, respectively, by controlling the gas-water synergy. Meanwhile, under the gas-water synergy displacement condition, the oil recovery is increasing with the tilt angle of the reservoir increasing and the distance of well from edge water decreasing. This enhanced oil recovery process is more sensitive to low-middle tilt angles and more effective for small distances. The results obtained from this study can be used to improve the exploitation strategies of tilted fault block reservoir with edge water.

The inter-salt argillaceous dolomite reservoirs in the central region of China contain large abundance of oil resources with ultra-low permeability and porosity. However, the oil wells in this area show a very quick reduction with the decline of formation pressure. This article aims to investigate the main possible reasons that affect oil well productivity in the target oilfield. This study begins with analysis of capillary microscopic model, core stress sensitivity experiments, and non-Darcy percolation experiments. The impact of effective stress on permeability and porosity of the reservoir was revealed in this article. The novel productivity model and productivity evaluation model which couples stress sensitivity and threshold pressure gradient were proposed. The analysis of capillary microscopic model shows stress sensitivity of permeability to be much greater than that of porosity during the process of depressurization. The core stress sensitivity experiments results indicate that permeability and effective stress show index relationship while porosity and effective stress show binomial relationship. Damage rate and recovery rate of permeability and porosity were put forward to describe the degree of influence of stress sensitivity on permeability and porosity. The models were used to investigate the factors that affect single well productivity for the target oilfield. Application of the proposed model to this tight oilfield indicates that, the degree of influence of stress sensitivity is much greater than that of threshold pressure gradient. In addition, the greater the stress sensitivity coefficient and threshold pressure gradient are, the greater the productivity reduction will be.

Special attention has recently been paid to shale oil and gas due to an increase in demand for unconventional hydrocarbons in the worldwide. In 2011, exploration wells were drilled in Bohai Bay Basin, East China, and well production tests for these wells indicate that the oil shale formation has a potential for further oil production. However, pore characteristics of oil shale have not been well understood because of its pore sizes ranging from nanometer (nm) to micrometer (μm), which are quite different from the pore sizes of sandstone reservoir. In this work, scanning electron microscope (SEM) images of shale cores sampled from Luojia formation were used for analysis of micro-pore sizes and structures. Mercury injection experiments were carried out to study pore characteristics and heterogeneity of the shale samples. It is found that the pore types of these shale samples mainly include organic pore, intergranular pore and intragranular pore. Hydraulic fractures and natural micro-fractures are the main types of fractures connecting network in shale rocks. The pore sizes of a shale rock sample from 25 to 400 nm and movable saturation of the non-wetting phase in the rock sample is only 0.12. Both pore sizes and movable saturation in the rock are much less than that of sandstone.

The tight gas reservoirs in the Southwestern part of China contain large abundance of gas resources with ultra-low permeability and porosity. However, the gas wells in this area show high early production rate but decline quickly, and follows by a long-term production at a lower rate. This paper aims to investigate the possible reason behind the production performance, and also reach a novel productivity model to describe the well performance in this area. This study begins with performing various formation damage experiments including salinity, velocity, acids, alkali, and stress on the core samples from this area. The formation damage through the measured permeability change in these experiments were evaluated and compared. The Non-Darcy effect of gas flowing through tight porous media is also investigated in this study. A novel model to evaluate productivity which couples the primary formation damage and Non-Darcy effect in this area is proposed based on the formation damage results and Non-Darcy effect. We finally apply the novel model to this gas field, and implement sensitivity analysis to find out the key parameters that affect the well productivity. Experimental results show that both salinity sensitivity and stress sensitivity lead to formation damage in this area. Comparing the degree of permeability decreasing suggest that stress sensitivity is the primary formation damage for the early quick production declines. Experimental results also show that there exists a threshold pressure for gas flowing through the tight porous media. Applications of the proposed model to this tight gas field and also for sensitivity analysis with the results indicate that, the degree of influence of stress sensitivity is much greater than that of threshold pressure gradient. In addition, the greater the stress sensitivity coefficient and threshold pressure gradient are, the greater the productivity declining rate will be.

In this paper, microscopic visualization devices and image processing techniques were used to conduct microscopic water flooding experiments. A novel classification criterion for residual oil during the water flooding process was established as follows: contiguous type, branched type, oil film type, columnar type, and droplet type. Correlations between the five types of residual oil saturation and water-cut were established. Also, the recovery improving potential for different production strategies have been investigated by water flooding experiments. The relationship between various types of residual oil saturation and injection velocity were obtained, with the former residual oil saturation decreasing to 16.09% during the injection process when the velocity was increased from 0.05 mL/min to 0.5 mL/min. However, with an increase in injection velocity, the saturation of contiguous residual oil type decreased first and then stabilized. The saturation of branched oil type monotonically decreased, but saturation of droplet oil type monotonically increased. Residual oil saturations were 22.62% and 9.69% before and after altering injection direction, respectively, which means residual oil recovery was increased by 12.93%. Some places were considered to be “dead oil regions” before altering injection direction with most of the contiguous and branched type residual oil in these areas been displaced out by altering injection direction. Altering the injection direction is a more effective method of enhancing oil recovery than improving injection velocity when the same volume of water is injected. The proposed method and prediction correlations were presented in this paper to provide a novel means to predict oil recovery and residual oil saturation types for water flooding reservoirs, which have strong plane and weak vertical heterogeneity.

Solvent-assisted steam flooding has gained popularity in heavy oil reservoir during recent years. Calculating asphaltene deposition is a key issue in developing heavy oil reservoirs, because asphaltene deposition can significantly reduce permeability by blocking pore throats. In this work, a comprehensive model of solvent assisted steam flooding for thin heavy oil reservoirs considering the influence of asphaltene deposition was proposed. The model is solved by IMPES (Implicit Pressure and Explicit Saturations) method. The amount of deposition is calculated through three mechanisms of entrainment, plugging deposition and surface deposition. Then, the effects of asphaltene deposition on well performance and permeability reduction were analyzed. Furthermore, the solubility parameter is used to investigate the effect of different solvents on alleviating the damage of asphaltene deposition for reservoir. The damage of asphaltene deposition for reservoir can decrease with the increase of solvent concentration. Finally, based on the analysis of oil production, it is found that butane assisted steam flooding is the most effective thermal method to improve the oil recovery. And injection parameters of butane assisted steam are also determined for an oil field by analysis of oil production. Based on the results in this paper, it may be extensive applicability and practical significance for determining the best solvent and reasonable injection parameters during the development of heavy oil reservoirs considering asphaltene deposition to enhance oil recovery.

The adsorbed methane in shale determines the geological reserves of shale gas and production of the well. Therefore, it is of great importance to clarify the microscopic mechanism of methane adsorption in shale for evaluating the geological condition and formulating exploitation plan. In this study, the experimental data and the simulation result were combined to research the microscopic mechanism of methane adsorption in shale. The experimental data for 99 groups of low-temperature nitrogen adsorption and methane isothermal adsorption were collected, to calculate the number of adsorption layers of methane in shale at the micro-level. The surface, microfracture and micropore structures of the organic matter in shale were constructed by graphite structure with the hydroxyl group. Thereafter, they were used to simulate the interaction potential of the organic matter on methane molecules and the adsorption layer's number by using the theory of intermolecular interaction potential field. Furthermore, the effects of different fracture widths and pore diameters on methane adsorption were analyzed and verified. The results show that the adsorption capacity of methane in shale is related to shale's structure, and the order of the adsorption capacity is surface

Formation deformation of oil reservoirs is a widespread phenomenon for unconsolidated or abnormal high-pressure formations due to the depletion of reservoir pressure in the process of oil recovery. It may not only result in formation damage, but also have an adverse influence on production performance. In this paper, the deformation behavior of formation and formation damage are analyzed by elastic, elastic–plastic and plastic theory of solid porous media, and a set of expressions is derived to describe the change in porosity and permeability caused by linear or nonlinear deformation. Based on the comprehensive study on deformation of reservoir rock and multiphase flow in porous media, a new three dimensional and three phase-flow mathematical model that is used to predict the changes of porosity and permeability is presented, and the model is solved by the finite-difference method and self-adaptive iterative technique. A field-scale numerical simulator written in FORTRAN code is developed to predict the change trend of porosity and permeability in elastic and elastic–plastic deformation range. The runs of an oil field example with five-spot patterns are calculated on the simulator, and the formation damage and its influence on the pressure profiles in the vicinity around production well are studied under the condition of linear and nonlinear deformation of a reservoir. This work implies that the deformation of oil formation may be elastic, elastic–plastic or plastic in actual oil formation during the oil exploitation. The declines of porosity and permeability induced by the deformation are completely recoverable only for elastic deformation. Furthermore, elastic–plastic and plastic deformation may occur in the vicinity of production wells in unconsolidated formations. It is found that the increase of deformation coefficients presented in this work results in a sharp pressure-drop funnels on the vertical cross profile, which can be interpreted by the permeability decline induced by rock deformation.

The effects of pressure on the gas viscosity and compressibility factor lead to a nonlinear partial differential equation for the flow in a gas reservoir even if the flow process follows Darcy’s law at isothermal conditions. For further study on gas flow performances in gas reservoirs, a mathematical model of gas flow is developed in this article. Exact analytical solutions of one-dimensional unsteady gas flow at low and high pressures in gas reservoirs are obtained by transferring the nonlinear partial differential equation into a nonlinear ordinary differential equation. The numerical solutions obtained by finite difference for two cases of lowand high-pressure condition are given to validate the analytical solutions presented in this work. The key parameters, such as viscosity index, permeability, and porosity, to determine the characteristic of pressure distribution in porous media are analyzed in this work. The solutions at high pressures imply that it leads to obvious errors for prediction pressure distribution when ignoring pressure’s effects on gas viscosity and compressibility factor for gas flow at high pressures in deep gas reservoirs. Both the increase in viscosity index and the decrease in permeability lead to an increase in pressure gradients along the distance.

Immiscible gas injection recovery is one of the most important methods used for EOR. However, it is very difficult to directly observe the flow of gas bubbles in the reservoir stratum. In our experimental work, we investigated visually the morphological configurations of gas bubbles migration, fragment, coalescence and trapping in different liquid-simulated porous media packs of glass beads. Also, the volume fraction of the trapped gas bubbles in the drainage process were measured. A fast video recording technique was used for the visual observations of the morphological characteristics of the rising gas bubbles in the saturated porous media. The obtained experimental images recorded reveal three types of the rising migration bubbles namely: free migration in the pore throat, attached wall migration on the beads and deformation migration. Additionally, coalescence and fragment have an interdependency for a rising gas bubble. The adsorption and capillary trappings are both two kinds of important trapping mechanisms, which determine the volume fraction of the trapped bubbles. The volume fraction of the trapped bubbles increases with an increment in the gas injection time and rates with the trapped bubbles fluctuating upward and downward due to the more coalescence and fragment after a long gas injection time/period. Lastly, the volume fraction of the trapped bubbles increases with a decrease in the inclination angles and porosities, which influences the areal sweep efficiency for enhanced liquid recovery in a porous media.

This paper focuses on the idea for enhancing oil recovery by CO2 injection into oil formation as well as reducing CO2 emission into the atmosphere. The mechanism of asphaltene flocculation during CO2 flooding in oil formations is analyzed and the regressive correlation between CO2 concentration and the amount of flocculated asphaltene for an oil sample is set up for coupling with the flow governing equations for the flocculated asphaltene transport in porous media. A three-dimensional multiphase mathematical model describing CO2 transport in oil reservoirs and asphaltene precipitation is presented for predicting CO2 flooding performances for enhanced oil recovery. The finite difference method and preconditioned conjugate gradient algorithm are used to solve the discrete nonlinear equation systems. A numerical simulation software is developed to study CO2 flooding performances and the effects of asphaltene precipitation on production behaviors. The numerical result indicates that water-cut decreases from initial 92.5% down to 40.3% after continuous CO2 injection for 10 years. It is also shown that 0.130 million tons of crude oil is displaced by CO2 injection in the 1 km2 of the reservoir within 10 years. Asphaltene precipitation leads to the decrease in permeability, and the decline in production rates.

A suspension of nanoscale polysilicon particles (NSPP) is injected into low permeable sand formations for reducing flow resistance of water. A set of instruments was assembled to get insights into the characteristics, adsorption and transport of the NSPP, wettability alteration, and its effects on two-phase flow performances in porous media. The TEM images show that the particles are approximate spheres with diameters from 10 to 200 nm. The NSPP could be adsorbed on the pore surfaces, and it looks like frost on the grains in the crossing section of sandstone. The wetting angle of water drop becomes far larger than 90o after the adsorption of the NSPP. It implies that the adsorption on pore surfaces leads to wettability alteration from water-wetness to oil-wetness. Wettability alteration is a major factor to change the percolation flow resistances of two phases, which has been verified by the change in relative permeabilities of the two phases. The flowable improvement of water results from the reduction i...