Multi-stage fractured horizontal wells are widely applied to develop tight reservoirs and shale gas reservoirs. Testing and evaluating well productivity are necessary in horizontal well multi-stage fracturing. Through analyzing the post-fracturing transient pressure data, key parameters affecting the productivity, such as effective fracture lengths, fracture conductivities, fracture skin factors and average formation permeability, can be estimated.
This paper presents a semi-analytical model based on Green's function and source/sink method to facilitate the transient pressure analysis for a multi-stage fractured horizontal well in a closed box-shaped reservoir. The fluid flow for a multi-stage fractured horizontal well includes the fluid flowing from the reservoir to fractures, the fluid directly from the reservoir to the horizontal wellbore, fluid flow inside the fractures and fluid flow inside the horizontal wellbore. Compared with previous models, fluid flow directly from the reservoir to the horizontal wellbore and pressure drop caused by pipe flow inside the wellbore are considered. In this model, fractures and horizontal wellbore are discretized into vertical plane segments and horizontal line segments, respectively. The fluid flow from the reservoir to fracture and that directly from the reservoir to the horizontal wellbore at each segment are modeled based on analytical solutions of vertical plane source and horizontal line source, respectively. The fluid flow inside the fracture is modeled based on 1-D linear flow. The fluid flow inside the horizontal wellbore is described with Penmatcha and Aziz's model (1999). Then, the flow equations are coupled together by using the flux- and pressure-continuity conditions on the interfaces.
The effects of the fracture lengths, fracture conductivities and fracture skin factors on the transient pressure behavior are studied and type curves are generated. The results suggested that in a tight or shale-gas reservoir, the transient pressure behavior during a testing period is mainly dominated by fracture stages, fracture lengths, conductivities and skin factors. The fluid flow directly from the reservoir into the horizontal wellbore reduces the pressure drop slightly. A field case is analyzed and reliable results are obtained. This model can be applied to optimize the fracture spacing and fracture length for a multi-stage fractured horizontal well.
This paper proposes a new methodology using condensation model to evaluate the early-period SAGD by interpreting the temperature falloff data in injector or producer obtained from fiber optics or thermal couples after the wells are shut-in. Based on the non-condensation model proposed before, the condensation model also assumes a circular hot-zone shape since in the early stage of SAGD operation, and characterize the system as composed of a steam-zone of steam temperature, a cold-zone of reservoir temperature and a transition-zone in between as the initial temperature distribution. Besides, the condensation model incorporates the effect of steam condensation on the condensation-front. The movement of steam condensation-front is calculated to account for the steam-zone shrinkage. Sensitivity analysis over this models indicates that the sizes of steam-zone, transition-zone and the observing location directly affect the temperature behavior at observation point. Synthetic case study shows that the temperature falloffs from condensation model and from simulation are in good agreement and suggests that condensation model can be used to estimate the chamber size at the early stage of SAGD. As is known, it is important to obtain an even steam chamber distribution along the horizontal wellbore to shorten the ramp-up time so that maximized economics can be achieved. In reality, the reservoir heterogeneity, the wellbore undulation and the operation condition make the steam chamber conformance impossible. Because of the ready-to-use temperature data and the semi-analytic solution, the condensation model proposed in this paper can provide quick and reliable estimation of the steam chamber size to help the engineers to monitor and optimize the chamber development thereafter.
Extra-heavy oil or bitumen wells are very difficult to start up and recover because of the high oil viscosity in cold production. It is necessary to get initial mobility by reducing the viscosity of oil or bitumen when the wells are drilled. Although there are mechanical ultrasonic stimulation technologies, the penetration of ultrasonic wave in the formation is very limited and their efficiency is not very good. Hot water or steam circulation is another option. However the heat loss in the wellbore is too significant to send enough heat to the targeted interval, specifically for deep reservoirs. Solvent could be a better option from both oil viscosity reduction and operation points of view. It can be injected into the well immediately after drilling for soaking, which is a convenient method to reduce viscosity without many complicated procedure as thermal methods. The concern for using solvent to reduce viscosity is selecting the optimal solvent. This paper studied the mixture of some typical extra-heavy oil and bitumen with solvent. After fully mixed with each other, viscosity reduction and potential precipitation have been investigated. Different solvents are discussed and recommended to reduce viscosity for new well start up and work-over.
A series of viscosity tests is conducted in the paper for heavy oil-solvent mixture under different temperatures to discuss the effect of three different solvents (diesel, ligarine and toluene) on viscosity reduction. Through these viscosity tests, the optimal solvent, temperature and solvent concentration for viscosity reduction are recommended. And it is found that after a solvent is placed in contact with heavy oil samples at any temperature in the range of 20 - 80C the reduction of viscosity can be significant. However, considering the economical effectiveness, diesel is not recommended. And 60-90 ligarine and toluene are better choices for starting up super heavy oil or bitumen wells. In addition, as to bitumen, due to its extremely high viscosity, using several times volume of solvent as the bitumen volume still can't have the viscosity reduce to a desired value. So these solvents tested in the experiments are not recommended for bitumen well starting up after drilling.
Diffusion-convection mass-transfer process in porous medium is one of the major enhanced oil recovery (EOR) mechanisms of Vapor extraction (VAPEX). Previous work tried Fick's Law to model the diffusion process, and mostly assumes the diffusion coefficient as a constant in the equation. However, the diffusion coefficient factually is a function of concentration, and thus the effect of its gradient should be included in the governing equation. In addition, bulk flow exist during the VAPEX especially during the solvent chamber rising phase, hence the process may be a diffusion-convection process rather than a pure diffusion process as presumed in previous works.
This paper proposes a new one-dimensional (1D) VAPEX mathematical model on the basis of diffusion-convection equation, gravity-based fluid flow equation (Darcy's law), and mass-conservation equation. The model is directed at a vertical thin cylindrical VAPEX process with injector and producer both setted at the bottom. The solvent chamber is considered as a two-phase area and the oil in it is completely saturated, while the matiral beyond the chamber is thought as in liquid phase. First, the diffusion-convection model is developed to obtain the concentration distribution in the transition zone; the boundary between solvent chamber and transiton zone is seen as moving with time. Second, the drainage velocity of the saturated oil in solvent chamber is calculated and combined with the mass conservation equation, to model the saturation of the oil phase changing with time. On the basis of the saturation model the oil production rate can be obtained.
The recovery factor profile is divided into two distinct stages: solvent diluting-dominated stage and saturated oil flowing-dominated stage. During the first stage, it is found the solvent chamber growing rate tends to be constant; the oil production rate is proportional to the square root of permeability, which constists with the existing VAPEX theoretical model. During the second stage, the production rate is linearly related to the 1.1-1.3 power of the model length rather than the square root of it. This agrees perfectly with the lab observations in previous work.
Electrical Resistive Heating (ERH) has been proposed as a thermal recovery method for heavy oil reservoirs with low environmental impact. ERH could potentially be an alternative to steam-related processes in the reservoirs which are not suitable for steam injection methods due to low incipient injectivity and formation incompatibility. Meanwhile, Vapor Extraction (VAPEX) has been tested as an environmentally sustainable oil recovery method in both lab scale and field scale. However, the field test results showed that this process is not efficient and economical due to low mass transfer and low horizontal well efficiency. This paper presents a hybrid process of ERH with Solvent Injection. The hybrid process could enhance horizontal well efficiency and overall oil production rate, with less environmental impact than other steam-related thermal processes. Numerical simulations were conducted to evaluate this process via CMG's STARS. Well pattern similar to that in classical SAGD process is used. The electrode is placed along with the producer or injector and solvent is injected from the injector. This process has three features which contribute to the enhanced oil flow: (1) the heat from producer establishes good communication between the injector and the producer by reducing viscosity; (2) the in-situ generated heat through ERH along with the horizontal wellbore is insusceptible to reservoir heterogeneity. Thereby the horizontal well conformity can be improved; (3) the solvent can reduce the viscosity of the heavy oil in unheated zone where the ERH can not reach; while it can also assist viscosity reduction of heavy oil in the heated zone. The factors affecting this hybrid process, such as electrode placement, voltage, well distance and heterogeneity effect, lateral pattern and water saturation, were also discussed in this paper. The simulation results showed that this hybrid process can improve the oil rate 2 to 5 times over VAPEX.
Vapour Extraction (VAPEX), a process to recover heavy oil by injecting vapourized solvent into a reservoir, has been extensively studied through small-scale 1-D and 2-D laboratory tests. Recently, a series of large-scale 3-D tests have been conducted by Saskatchewan Research Council (SRC). In this study, 2-D tests were conducted under the same conditions as those for the 3-D tests; then, numerical simulation models were investigated to reduce the uncertainty in upscaling the results from 2-D tests to 3-D tests. This helps to better understand the uncertainty in predicting the field-scale VAPEX performance.
Plover Lake heavy oil was used in the tests, and the sandpack permeability was about 4.4 Darcy. In each test, the initial waterflooding was conducted prior to the subsequent solvent injection. Then, a numerical model was established to simulate the 2-D test. History match of the 2-D test was conducted by tuning the uncertainties such as the relative permeability, capillary pressure, solubility, and the wall effect in sand-packing. Afterwards the tuned parameters were applied to predict the 3-D test performance. Through comparison of the predicted and experimental results in the 3-D test, the capability of predicting up-scaled VAPEX processes through numerical simulation was examined, and the differences between physical and numerical modeling were identified.
The results show that the waterflooding performance can be successfully predicted, whereas the uncertainty in upscaling the VAPEX process is large. In the waterflooding period, the predicted oil recovery factor was 25.78% compared with 23.4% in the 3-D test. In the VAPEX process, the difference between the predicted and measured oil recovery factors was in the range of 0.75-25.14%, depending on the different combination of uncertain parameters. This fact indicates that different scales of physical modeling are required in order to reduce the uncertainties in predicting the field-scale VAPEX performance.