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Abstract Low salinity waterflooding is an emerging EOR technique in which the salinity of the injected water is controlled to improve oil recovery over conventional higher salinity waterflooding. Corefloods and single well chemical tracer tests have shown that low salinity waterflooding can improve basic waterflood performance by 5 to 38%. This paper describes a model of low salinity flooding that can be used to evaluate projects, shows the implications of that model, demonstrates its use to represent corefloods and single well tests as well as field scale simulations, and gives insight into the reservoir engineering of low salinity floods. The model represents low salinity flooding using salinity dependent oil/water relative permeability functions resulting from wettability change. This is similar to other EOR modelling and conventional fractional flow theory can be adapted to describe the process in one dimension for secondary and tertiary low salinity waterflooding. This simple analysis shows that while some degree of connate water banking occurs it need not hinder the process. Because mixing of injected water with in situ water delays the attainment of low salinity, potentially preventing attainment of low salinity all together if very small slugs of low salinity water are used, care must be taken in representing mixing appropriately in interpreting data and in constructing models. The use of numerical dispersion to represent physical dispersion in 1D, radial and pattern simulations of this process is demonstrated, i.e. coarse simulations are shown to give the same result as fine grid simulations with appropriately large physical dispersion. In many applications, the fine grid simulation necessary to represent appropriate levels of dispersion is not practical and pseudoization is necessary. We demonstrate that this can be done by changing the salinity dependence and shapes of relative permeability curves. Introduction Waterflooding is widely used to improve recovery from oil reservoirs but, except to avoid formation damage, is largely designed without regard to the composition of the brine injected. Yildiz and Morrow1 showed that showed that changes in injection brine composition can improve recovery, thereby, introducing the idea that the composition of the brine could be varied to optimize waterflood recovery. Tang and Morrow2–5 built on this idea by demonstrating the benefit lowering brine salinity has on oil recovery. BP has carried out an extensive research programme on low salinity injection which has thus far included more than 20 reservoir condition core floods on a range of sandstone reservoirs from its global portfolio both in secondary and tertiary mode, more than 10 single well chemical tracer tests (SWCTT), and a log inject log test. This program has resulted in a series of publications5–8 and the registration of the LoSal™ EOR process trademark. These tests have shown improvements of the oil recovery ofwaterflood process efficiency by 5% to 38% by using low salinity water of the waterflood reserves, or corresponding reductions in residual oil saturation of 3 to 17% pore-volume. The purpose of this work is to present a simple extension to waterflood simulators that can be used to translate corefloods or SWCTT into field scale estimates of low salinity waterflood oil recovery and demonstate this with examples from a sandstone reservoir.
Summary Low‐salinity waterflooding (LSWF) is a promising process that could lead to increased oil recovery. To date, the greatest attention has been paid to the complex oil/water/rock chemical reactions that might explain the mechanisms of LSWF, and it is generally accepted that these result in behavior equivalent to changing oil and water mobility. This behavior is modeled using an effective salinity range and weighting function to gradually switch from high‐ to low‐salinity relative permeability curves. There has been limited attention on physical transport of fluids during LSWF, particularly at large scale. We focus on how the salinity profile interacts with water fronts through the effective salinity range and dispersion to alter the transport behavior and change the flow velocities, particularly for the salinity profile. We examined a numerical simulation of LSWF at the reservoir scale. Various representations of the effective salinity range and weighting function were also examined. The dispersion of salinity was compared with a theoretical form of numerical dispersion based on input parameters. We also compared salinity movement with the analytical solution of the conventional dispersion/advection equation. From simulations we observed that salinity is dispersed as analytically predicted, although the advection velocity might be changed. In advection‐dominated flow, the salinity profile moves at the speed of the injected water. However, as dispersion increases, the mixing zone falls under the influence of the faster‐moving formation water and, thus, speeds up. To predict the salinity profile theoretically, we have modified the advection term of the analytical solution as a function of the formation- and injected‐water velocities, Péclet number, and effective salinity range. This important result enables prediction of the salinity transport by this newly derived modification of the analytical solution for 1D flow. We can understand the correction to the flow behavior and quantify it from the model input parameters. At the reservoir scale, we typically simulate flow on coarse grids, which introduces numerical dispersion or must include physical dispersion from underlying heterogeneity. Corrections to the equations can contribute to improving the precision of the coarse‐scale models, and, more generally, the suggested form of the correction can also be used to calculate the movement of any solute that transports across an interface between two mobile fluids. We can also better understand the relative behaviors of passive tracers and those that are adsorbed.
A three-dimensional hydrodynamic multi-purpose model for coastal and shelf seas COHERENS is applied to investigate the transport and dispersion of the heated and concentrated brine discharged from the Huangdao Power Plant situated on the western coast of Jiaozhou Bay. The values of time series of current velocity and water surface elevation given by the simulation have a good agreement with observed data. This indicated that the numerical model provided a fair simulation of the coastal flow in Jiaozhou Bay and were thus available for predicting heated and concentrated brine dispersion in the coastal water. The model can be applied to appropriately evaluate the locations of intakes and outlets of the power plants with seawater desalination processes and minimize the adverse influence on the coastal areas. INTRODUCTION Problem Background Seawater desalination has been a solution to water shortages in the field of drinking and industrial matter for several decades. In general, the salt content of water used in industrial production is no more than 0.05‰～ 2‰. In order to make use of seawater and relieve water shortage, the production of electricity is popularly connected with water. Thus, the power plant and seawater desalination are usually associated with each other, especially in recent years. Even though the processes of seawater desalination contribute to humanity as well as to nature preservation, they are also accompanied adverse environmental effects. However, these effects can be minimized through the appropriate planning. There are high temperature and high salt content in the effluent discharged from seawater desalination processes. The concentrations of the brines are usually found to be double or close to double that of natural seawater. In the case of evaporation methods, thermal pollution is also produced. Although the concentrate from thermal processes such as Multi-Stage Flash Seawater Desalination System (MSF) and Multi Effect Distillation (MED) is typically mixed with cold water prior to discharge, the dilution of concentrate results in a final discharged effluent is still more than the receiving water in temperature and in salinity.
Abstract The conventional method for describing transport of solutes such as salt, polymer and tracers is to use the mass conservation law. In simulation of this law for Low Salinity Water Flooding (LSWF), the effective salinity range defines how salt affects the mobility of water and appears to be crucial for controlling fluid movement. In this study, we examined the non-linear feedback between salt concentration movement and the low salinity water front as a function of physical and numerical dispersion, in combination with the effective salinity range, and we investigated how the front speeds were altered. We examined a numerical model of the mass conservation law to simulate LSWF at the reservoir scale. The cell sizes and the time steps were chosen to control the numerical dispersion coefficient in place of physical diffusion. A range of diffusion coefficients was considered along with various representations of the effective salinity range and the function that controls the effect that salt has mobility. The latter has been shown to be variable in the literature. We compared simulations to the analytical solution of solute transport obtained for the diffusion-advection equation assuming a fixed flowing velocity. We observed that the salinity front moved faster than was predicted by the analytical solution and this effect was increased the further the effective salinity range was set below the connate water salinity. In this case, the higher salt concentrations lay in the faster moving water (the connate water front), which also speeded up. This was very much a dispersion related effect, with the variation of velocity growing as the salt concentration spread out. By implementing many numerical tests, we obtained a modification to the advection term in the conventional mass conservation law of solute transport. This term depends on the Peclet number, the velocities of the high and low salinity fronts and the effective salinity as a proportion to the connate water salinity. In an advection-diffusion system, these factors usually affect only the advection term (the front velocity), while the diffusion term is unchanged. From numerical tests, we can now rapidly predict the movement of the salt front by this newly derived modification of the analytical solution.
Abstract The Alta field in the Barents Sea was discovered in 2014. The reservoir formation is primarily carbonate rocks with high formation water salinity. Extensive waterflooding processes have led to an approximately 200-m rise of water level. The complexities and uncertainties regarding imbibition, current free water level, and pseudo fluid contacts within the field translate into uncertainty in the hydrocarbon volume estimation. Initial, triple-combo-based petrophysical evaluations have already been updated using advanced log measurements, as reported in an earlier publication. The evaluation is now consolidated by using two new techniques relying on advanced spectroscopy logging and combination with dielectric dispersion logging. Their objective is to further reduce the uncertainty in water saturation associated with variable apparent water salinity. The present contribution proposes a workflow that relies on two novel techniques. The first technique is a direct quantitative measurement of formation chlorine concentration from nuclear spectroscopy, which helps resolve the formation's apparent water salinity and provides a way to calibrate formation matrix sigma. The second technique relies on the existing combined inversion of dielectric dispersion and formation sigma, including explicitly invasion effects. This second technique benefits from the first technique's insight to adjust sigma interpretation and provide bounds for possible salinity variations. The workflow provides robust flushed and unflushed zone salinities, here the most uncertain and variable parameter, combined with accurate estimations of virgin and residual hydrocarbon saturations. The quantification of dielectric textural parameters describing how the water is shaped inside the formation is also improved, contributing to the improvement of virgin zone hydrocarbon saturation estimation.