Nanotechnology is one of the modern techniques that can be used for enhancing the oil recovery. Enhanced oil recovery (EOR) is mainly used after oil production declination by chemically altering the injection water. However, it is very important to have an environmentally friendly method to enhance oil recovery. A possible method is to use nanofluids that include nanosilica-polymer (NFs) which contain mainly sandstone ingredients. This research is mainly an experimental investigation of the usage of several nanofluids with silica particles for enhanced oil recovery. Nanofluid injection is performed in core plugs and the oil recovery is compared with the oil recovery obtained with synthetic sea water (SSW) injection. Both nanofluid and SSW are injected in secondary mode. Five cleaned and dried Berea sandstone cores were used in the core flooding experiments. First, secondary recovery was applied on all cores by SSW injection. Then the cores were re-cleaned and re-dryed to be prepared for the secondary recovery by using 4 different types of nanofluids with the same concentration of 0.1 wt% as NFs. In this research, it was important to use exactly the same rock in both the SSW and nanofluid flooding to avoid any effect of pore structure on the oil recovery. The research showed that the best nanofluid contained nanoparticles of silica-alumina. This nanofluid gave the highest oil recovery and altered the wettability from water wet to strongly water wet due to the ionic interactions. The ultimate oil recovery was increased to 10.4% of OOIP (original oil in place) compared to SSW injection. In addition to investigating the quantitative effect of the use of several nanofluids with different nanoparticles sizes and surface modifications on oil recovery we also applied Scanning Electron Microscopy (SEM) to study pore blockage, log jamming, and emulsions between NFs and crude oil.

The injection of Sulphonated-smart water (SW) could be an attractive application as it results in the formation of a mechanically rigid oil-water interface, and hence possible higher oil recovery in combination with the polymer. Therefore, detailed experimental investigation and fluid flow analysis through porous media are required to understand the possible recovery mechanisms. This paper evaluates the potential influence of Sulphonated/Polymer water injection in oil recovery by coupling microfluidics and core flooding experiments. The possible mechanisms are evaluated utilizing a combination of experiments and fluids. Initially, synthetic seawater (SSW) and Sulphonated-Smart water (SW) were optimized to be used in combination with a viscoelastic HPAM polymer. Fluid characterization was achieved by detailed rheological characterization focusing on steady shear and in-situ viscosity. Moreover, single and two-phase core floods and micromodels experiments helped to define the behavior of different fluids. The data obtained was cross-analyzed to draw conclusions on the process effect and performance. First, Sulphonated/polymer water solutions showed a slight decrease in the polymer shear viscosity as compared to the SSW-polymer. Similar behavior was also confirmed in the single-phase core flood-through the differential pressure, looking at the in-situ viscosity. Second, on the one hand, smart water produced only ~3% additional oil recovery as compare to the SSW through micromodel due to improved interfacial viscoelasticity, where no local wettability alteration was observed in the porous media. On the other hand, core flood experiments using SW led to ~12% additional oil as compare to SSW. This excessive extra recovery in core flood compare to micromodel could be due to the combined effect of interfacial viscoelasticity and wettability alteration. Micromodel is coat with a hydrophobic chemical; hence, wettability becomes hard to be altered through SW while in the core flood it is dominated with ionic exchange (local wettability alteration). Finally, a combination of SW with polymer flood can lead to ~6% extra oil as compare to the combination of polymer flood with SSW. Overall, coupling microfluidics with core flooding experiments confirmed that IFV and wettability alteration both are the key recovery mechanisms for SW. The evaluation confirmed that the main recovery mechanisms of smart-water injection are interfacial viscoelasticity and wettability alteration. Furthermore, it confirmed that the combination of SW with polymer flood could sweep the reservoir efficiently resulting in higher oil recovery. This topic has been addressed in the literature with mixed results encountered.

The waterflood performance depends on two major components: the sweep efficiency and displacement efficiency. The sweep efficiency depends on proper understanding of the vertical and lateral distribution of reservoir properties. One of the methods to check and calibrate this understanding is to perform pressure interference test (PIT) in few cross-well intervals. Unfortunately, a proper implementation of traditional step-response PIT with objective for quantitative interpretation requires shutting-down the wells, preferably the whole area around receiving well resulting in punishing production deferment. This was a bottle-neck for wide spread of quantitative PIT for many decades. This paper describes the experience with a specific implementation of PIT – Pressure Pulse Code Test ( PCT ) – which allows data acquisition under scheduled production. The trade-offs are usually acceptable: longer field operations, high resolution downhole gauges, more complex and longer data processing, advanced software tools and as result – a more expensive service, which anyway comes much cheaper than production deferment. The paper shows how PCT can be qualified using the synthetic field tests and real field tests and shows a typical application of PCT findings in one of the Eastern Siberian carbonate reservoirs.

Injection Fall-Off (IFO) testing is one of the most important methods to help monitor injector performance over time in waterfloods, water disposal operations, polymer floods, etc. IFO tests provide information about, amongst others, k*h, skin, reservoir transmissibility, and mobility contrasts. Analysis of the early-time period of such tests also can yield estimates of length and height of fractures that are induced during injection. There is however, one important parameter that cannot be estimated from IFO tests, which is the Fracture Closure Pressure (FCP) which is generally considered to be a measure for minimum principal in-situ stress. In this work, we present exact 3D simulations of hydraulic fracture propagation, followed by fracture closure as a result of shut-in and after-closure reservoir flow. The simulations focus on the details of valve closure at the wellhead followed by propagation and (repeated) reflection of the closure-induced pressure pulse (‘water hammer’) whilst at the same time the fracture is gradually closing. The simulated post shut-in pressure decline trends which are the combined result of water hammer, fracture closure and reservoir fluid flow have been compared with field data. The main result that consistently emerged from our simulations and their comparison with field data is that the water hammer disappears as soon as the fracture is completely closed. This can be explained by the fact that the magnitude of a water hammer following injector shut-in strongly increases with the total ‘system’ (wellbore plus fracture) compliance (storage), as is evidenced from our simulations. Since often, the system compliance for an open fracture is an order of magnitude higher than for a closed fracture, fracture closure itself results in a practical disappearance of water hammer. Thus, identification of the point of water hammer disappearance after shut-in allows one to estimate FCP.

Two global challenges are an increase in carbon dioxide (CO 2 ) concentration in the atmosphere, causing global warming and an increase in energy demand ( UNFCCC, 2015 ; EIA, 2018 ). Carbon Capture and Storage (CCS) is believed to be a major technology to considerably reduce CO 2 emissions ( Budinis et al. , 2018 ). Applying this technology, the anthropogenic CO 2 could be injected into depleted reservoirs and permanently stored in the subsurface. However, standalone CCS projects may not be economically feasible due to CO 2 separation, transportation and storage costs ( Pires et al. , 2011 ). On the other hand, one of the most efficient Enhanced Oil Recovery (EOR) methods is carbon dioxide injection ( Holm, 1959 ). Therefore, a combination of CO 2 -EOR and storage schemes could offer an opportunity to produce additional oil from depleted reservoirs and permanently store CO 2 in the subsurface in an economically efficient manner. In this study, a depleted sandstone reservoir located in the Norwegian Continental Shelf (NCS) is used. An innovative development scenario is considered, involving two phases: CO 2 storage phase at the beginning of the project followed by a CO 2 -EOR phase. The objective of this paper is to evaluate the effect of different injection methods, including continuous gas injection (CGI), continuous water injection (CWI), Water Alternating Gas (WAG), Tapered WAG (TWAG), Simultaneous Water Above Gas Co-injection (SWGCO), Simultaneous Water and Gas Injection (SWGI) and cyclic SWGI on oil recovery and CO 2 storage potential in the depleted reservoir. A conceptual 2D high-resolution heterogeneous model with one pair injector-producer is used to investigate the mechanisms taking place in the reservoir during different injection methods. This knowledge is applied in a field scale, realistic 3D compositional reservoir model of a depleted sandstone reservoir in the NCS including ten oil producers and twenty water/gas injectors. The simulation results demonstrate that innovative development scenario is viable to improve oil recovery and storage capacity in the depleted reservoirs. Different injection scenarios are benchmarked, and cyclic SWGI method is found to be the most efficient scenario in enhancing oil recovery and employing the highest capacity for CO 2 storage.

We investigate the effect of heterogeneous petrophysical properties on Low Salinity Water Flooding (LSWF). We considered reservoir scale models, where the geological properties were obtained from a giant Middle East carbonate reservoir. The results are compared against a typical sandstone model. We simulated low salinity induced wettability changes in field scale models in which the petrophysical properties were randomly distributed with spatial correlation. We examined a wide range of geological realisations which mimic complex geological structures. Sandstone was simulated using a log-linear porosity-permeability relation with fairly good correlation. A carbonate reservoir from the Middle East was simulated where a much less correlated porosity permeability relationship was obtained. The salinity of formation water was set to typically observed values for the sandstone and carbonate cases. A number of simulations were then carried out to assess the flow behaviour. We have found that the general trend of permeability-porosity correlation has a key role that could mitigate or aggravate the impact of spatial distributions of petrophysical properties. We considered models with a log-linear permeability-porosity correlation, as generally observed for sandstone reservoirs. These are likely to be directly affected by the spatial distribution more than models with a power permeability-porosity correlation, which is often reported for flow units of carbonate reservoirs. The scatter of data in the permeability-porosity correlations had a relatively small impact on the flow performance. On the other hand, the effect of heterogeneity decreases with the width of the effective salinity range. Thus, uncertainty in carbonate reservoirs arises due to the ambiguity of spatial distribution of permeability and porosity would be less affects the LSWF predictability than in sandstone case. Overall, the incremental oil recovery due to LSWF was higher in the carbonate models than the sandstone cases. We observe from uncertainty analysis that the formation waterfront was less fingered than the low salinity waterfront and the salinity concentration. The dispersivity of salinity front and the water cut can be estimated for models with various degrees of heterogeneity. The outcome of the study is a better understanding of the implications of heterogeneity on LSWF. In some cases the behaviour can appear like a waterflood in very heterogeneous cases. It is important to assess the reservoir effectively to determine the best business decision.

Polymer flooding is a widely applied enhanced oil recovery (EOR) technique using soluble polymers to increase the injection water viscosity and therefore enhance the sweep efficiency in the field. Biopolymers are an environmentally friendly alternative to synthetic polymers and can have good salt- and temperature tolerance like the polymer Schizophyllan. Because biopolymers are often biodegradable, it is important to protect them against potential microbial degradation at subsurface conditions, especially in the near wellbore region consisting of the first few meters after injection. Three individual sandpack experiments were performed to assess biodegradation of Schizophyllan at original reservoir conditions. An enriched, biodegrading microbial community was injected into all sand packs and two treatment options were tested: a) adding the biocide Bacillat after a mature degrading biofilm was developed; b) adding biocide prior to mature biofilm formation. Different biocide concentrations were tested. Rest viscosity (i.e. level of biodegradation) was determined by measuring viscosity injected and produced from the sandpack columns. Various microbial (cell numbers, metabolite production and identity) and petrophysical (differential pressure, permeability) parameters were assessed during the experiments. The results show that the relative loss in the effluent viscosity was lower than 10 % when 375 ppm biocide was added to the injection fluid 24 hours after the inoculation period (prior to mature biofilm development). Microbial cell counts were low and byproducts because of degradation could not be measured even after 80 days of injection. The same concentration proved to be ineffective to improve the effluent viscosity (90 % viscosity loss) measured in the column with a mature biofilm. Successive concentration increase (375, 750 and 1900 ppm) did not have a significant effect on viscosity maintenance and were not able to inactivate biodegradation. Initial high biocide concentrations (750 ppm and 1900 ppm) could not protect the polymer in the presence of an active biofilm Furthermore, degradation of the biopolymer could not be prevented by using 200 ppm biocide at the start of injection before biofilm buildup. This shows a strong resistance and adaptability of the biofilm towards the used biocide. Permeability of the sand packs containing a growing biofilm decreased drastically, indicated by a continuous increase in differential pressure. Our study shows that Schizophyllan could be protected from bio-degradation if the right biocide concentration is used at the beginning of the injection period. The sandpack study shows the importance of a well-designed biopolymer protection strategy prior to field implementation and the need for an early mitigation of biodegradation and/or biofilm formation. Such experiments enable the possibility to test the different biocidal treatments under reservoir-like conditions and predict biopolymer stability in the field.

Carbonates are known to be heterogeneous. In this paper, we will focus on characterising inter-well connectivity by applying a multi-dimensional approach to production data analysis along with integration of inter-disciplinary data for a Brazillian carbonate reservoir. Results of the analysis are used for interpretation of a noisy 4D seismic data to locate sweet spots. This unique integrated approach characterizes inter-well connectivity from four perspectives: (1) determine reservoir quality (2) identify source of water production (3) tracking of injected fluid's flow path (4) verify impact on 4D seismic response. We will show how the quality of a carbonate reservoir and its aquifer strength can be verified with well logs, pressure depletion rates and production behaviour. The use of sensitivity analysis in mechanistic models will also be shared to analyse the impact of heterogeneity on production behaviour. Using Chan's (1995) water-oil-ratio diagnostic plots, the source of water production will be identified as well. Explanation of analysis of well chronology, bubble maps of water cut will also be provided for tracking of injected fluid flow paths. Finally, interaction of production parameters between well-pairs and resistance modelling will be used to evaluate inter-well connectivity, and verified with 4D seismic data. Findings from all the analysis in the integrated approach are summarized into an inter-well connectivity metric, which is used as a reference for production and seismic history matching and interpretation of the noisy 4D seismic data. The integrated data analysis shows that the sweet spot corresponds with softening on the 4D seismic map, un-swept by injectors as it is located on a structural high southeast of the reservoir. This paper offers a comprehensive analysis to characterize important reservoir characteristics (such as thief zones and tight streaks). It will also emphasize ways to integrate inter-disciplinary data, and showcase various visualization perspectives to fortify and enhance the importance of data integration.

Polymer flooding offers the potential to recover more oil from reservoirs but requires significant investments which necessitate a robust analysis of economic upsides and downsides. Key uncertainties in designing a polymer flood are often reservoir geology and polymer degradation. The objective of this study is to understand the impact of geological uncertainties and history matching techniques on designing the optimal strategy and quantifying the economic risks of polymer flooding in a heterogeneous clastic reservoir. We applied two different history matching techniques (adjoint-based and a stochastic algorithm) to match data from a prolonged waterflood in the Watt Field, a semi-synthetic reservoir that contains a wide range of geological and interpretational uncertainties. An ensemble of reservoir models is available for the Watt Field, and history matching was carried out for the entire ensemble using both techniques. Next, sensitivity studies were carried out to identify first-order parameters that impact the Net Present Value (NPV). These parameters were then deployed in an experimental design study using a Latin Hypercube to generate training runs from which a proxy model was created. The proxy model was constructed using polynomial regression and validated using further full-physics simulations. A particle swarm optimisation algorithm was then used to optimize the NPV for the polymer flood. The same approach was used to optimise a standard water flood for comparison. Optimisations of the polymer flood and water flood were performed for the history matched model ensemble and the original ensemble. The sensitivity studies showed that polymer concentration, location of polymer injection wells and time to commence polymer injection are key to optimizing the polymer flood. The optimal strategy to deploy the polymer flood and maximize NPV varies based on the history matching technique. The average NPV is predicted to be higher in the stochastic history matching compared to the adjoint technique. The variance in NPV is also higher for the stochastic history matching technique. This is due to the ability of the stochastic algorithm to explore the parameter space more broadly, which created situations where the oil in place is shifted upwards, resulting in higher NPV. Optimizing a history matched ensemble leads to a narrow variance in absolute NPV compared to history matching the original ensemble. This is because the uncertainties associated with polymer degradation are not captured during history matching. The result of cross comparison, where an optimal polymer design strategy for one ensemble member is deployed to the other ensemble members, predicted a decline in NPV but surprisingly still shows that the overall NPV is higher than for an optimized water food. This indicates that a polymer flood could be beneficial compared to a water flood, even if geological uncertainties are not captured properly.

Optimal field development and control aim to maximize the economic profit of oil and gas production. This, however, results in a complex optimization problem with a large number of correlated control variables at different levels (e.g. well locations, completions and controls) and a computationally expensive objective function (i.e. a simulated reservoir model). The typical limitations of the existing optimization frameworks are: (1) single-level optimization at a time (i.e. ignoring correlations among control variables at different levels); and (2) providing a single solution only whereas operational problems often add unexpected constraints likely to reduce the ‘optimal’, inflexible solution to a sub-optimal scenario. The developed framework in this paper is based on sequential iterative optimization of control variables at different levels. An ensemble of close-to-optimum solutions is selected from each level (e.g. for well location) and transferred to the next level of optimization (e.g. to control settings), and this loop continues until no significant improvement is observed in the objective value. Fit-for-purpose clustering techniques are developed to systematically select an ensemble of solutions, with maximum differences in control variables but close-to-optimum objective values, at each level of optimization. The framework also considers pre-defined constraints such as the minimum well spacing, irregular reservoir boundaries, and production/injection rate limits. The proposed framework has been tested on a benchmark case study, known as the Brugge field, to find the optimal well placement and control in two development scenarios: with conventional (surface control only) and intelligent wells (with additional zonal control using Interval Control Valves). Multiple solutions are obtained in both development scenarios, with different well locations and control settings but close-to-optimum objective values. We also show that suboptimal solutions from an early optimization level can approach and even outdo the optimal one at the higher-level optimization, highlighting the value of the here-developed multi-solution framework in exploring the search space as compared to the traditional single-solution approaches. The development scenario with intelligent completion installed at the optimal well location and optimally controlled during the production period achieved the maximum added value. Our results demonstrate the advantage of the developed multi-solution optimization framework in providing the much-needed operational flexibility to field operators.

Much work has been done on hydraulic-fracturing as a well stimulation technique but our understanding of formation damage due to fracturing is limited. This is due to inherent complexity of shale-water interactions under subsurface conditions. Damage is triggered by cold and low-salinity water invasion into the formation. Here, we introduce the formation damage mechanisms as a multi-physics/chemistry problem developing in a region near the fracture-matrix interface. Using high-resolution flow simulation models, we investigate the mechanisms and their impact on natural gas production. The simulation model includes geo-mechanically fully coupled non-isothermal multi-component two-phase flow equations that are developed for a multi-scale porous medium representative of the shale formations. We consider the occurrence of formation damage during two consecutive periods: well shut-in period which is considered to begin with the completion of fracturing and extending 1-2 days; followed by water flow-back and gas production period which takes months. During the early shut-in period, cold water invasion leads to thermal contraction of the matrix and reduces the normal mean stress. These changes improve the formation permeability temporarily, they may create secondary fractures, and modify the capillary pressure and saturations in the water invaded zone. These thermal effects are reduced rapidly, however, due to heat supplied by the reservoir. Osmosis pressure and the associated clay swelling cause the formation matrix to absorb fracturing water, reduce the matrix permeability, and amplify the capillary pressure/saturations. In summary, the well goes to the flowback and production with modified near-fracture conditions. During the water flowback the water saturation near the fracture-matrix interface increases; hence, liquid blockage effect on the gas flow becomes larger than that predicted based on the water imbibition during the shut-in only. This is due to capillary-end-effect developing near the interface during the water flow-back, when the fracturing water is displaced by the gas, i.e., drainage. Clay swelling and stress change continue during the withdrawal of the fluids. Consequently, we observe significant impairment in gas production rates. Only a fraction (<20%) of the injected water is ultimately produced back from the shale gas wells; the rest stays in the fractures and invades into the formation. Our simulation work shows that it is mainly the water in the fractures that are produced. The rest stays in the fractures due to relative permeability effects therein, and in the matrix as capillary-bound water due capillary end effect and to clay-swelling.

Various physico-chemical processes are affecting Alkali Polymer (AP) Flooding. Core floods can be performed to determine ranges for the parameters used in numerical models describing these processes. Because the parameters are uncertain, prior parameter ranges are introduced and the data is conditioned to observed data. It is challenging to determine posterior distributions of the various parameters as they need to be consistent with the different sets of data that are observed (e.g. pressures, oil and water production, chemical concentration at the outlet). Here, we are applying Machine Learning in a Bayesian Framework to condition parameter ranges to a multitude of observed data. To generate the response of the parameters, we used a numerical model and applied Latin Hypercube Sampling (2000 simulation runs) from the prior parameter ranges. To ensure that sufficient parameter combinations of the model comply with various observed data, Machine Learning can be applied. After defining multiple Objective Functions (OF) covering the different observed data (here six different Objective Functions), we used the Random Forest algorithm to generate statistical models for each of the Objective Functions. Next, parameter combinations which lead to results that are outside of the acceptance limit of the first Objective Function are rejected. Then, resampling is performed and the next Objective Function is applied until the last Objective Function is reached. To account for parameter interactions, the resulting parameter distributions are tested for the limits of all the Objective Functions. The results show that posterior parameter distributions can be efficiently conditioned to the various sets of observed data. Insensitive parameter ranges are not modified as they are not influenced by the information from the observed data. This is crucial as insensitive parameters in history could become sensitive in the forecast if the production mechanism is changed. The workflow introduced here can be applied for conditioning parameter ranges of field (re-)development projects to various observed data as well.

Cocurrent spontaneous imbibition is an important driving mechanism for oil (and gas) production in naturally fractured reservoirs, especially when matrix blocks are partially covered by both a wetting and a non-wetting phase (assumedly water and oil in this work). A 1D model is considered where water covers one side (inlet) and oil the other (outlet). Water then imbibes and displaces oil, mainly co-currently towards the outlet, spontaneously driven by capillary forces, but also to some extent counter-current production takes place at the inlet. The behavior of this system is described using (1) an advection-capillary diffusion transport equation combined with (2) a pressure equation. The pressure equation is solved to continuously update the total velocity in the advection term of the first equation. This system is tightly coupled and must be solved simultaneously to get solutions of pressures and saturations vs distance and time. Experimental and numerical works have indicated that the saturation profile is comparable with a Buckley-Leverett solution (obtained for forced displacement in absence of capillary forces). The aim of this work is to use the Buckley-Leverett profile explicitly to solve the pressure equation. This, combined with the boundary conditions will provide an analytical solution for recovery as function of time until the saturation front reaches the outlet. A solution is also suggested after the outlet is reached which corrects the Buckley- Leverett solution to maintain the imbibed water inside the system in agreement with the co-current spontaneous imbibition process and preserve continuity in recovery and spatial saturation profiles. For early times a numerical calculation is required based on the Buckley-Leverett profile to generate an effective total mobility and an effective capillary pressure. The solution can then be calculated explicitly. At late times an ordinary differential equation must be solved and the mentioned parameters change with time. The suggested solution is compared against numerical simulations. The solution provides a direct and accurate estimate of the time scale for the water front to reach the outlet and shapes of the recovery profile and was demonstrated to scale cocurrent imbibition recovery. It is shown that imbibition rate can increase, decrease and stay constant with time based on a derived effective mobility ratio which also can be used for evaluating effectiveness of displacement as it incorporates the entire saturation functions. Square root of time recovery is a special case only seen for very high oil mobility. It is demonstrated that co-current imbibition scales with the square of length both at early and late times. To our knowledge, previous analytical solutions have only considered infinite-acting systems, are limited to piston-like displacement assumptions or have focused only on the period before the outlet boundary is reached. They are also often based on implicit formulations that do not provide much more insight than numerical simulations. In addition to scaling recovery time, more understanding is given to the period after the outlet boundary is reached.

Many oil reservoirs worldwide have cycle dependent oil recovery either by design (e.g. WAG injection) or unintended (e.g. repeated expansion/shrinkage of gas cap). However, to reliably predict oil recovery involving three-phase flow process, a transformational shift in the procedure to model such complex recovery method is needed. Therefore, this study focused on identifying the shortcomings of the current reservoir simulators to improve the simulation formulation of the cycle-dependent three-phase relative- permeability hysteresis. To achieve this objective, several core-scale water-alternating-gas (WAG) injection experiments were analysed to identify the trends and behaviours of oil recovery by the different WAG cycles. Furthermore, these experiments were simulated to identify the limitations of the current commercial simulators available in the industry. Based on the simulation efforts to match the observed experimental results, a new methodology to improve the modelling process of WAG injection using the current simulation capabilities was suggested. Then the WAG injection core-flood experiments utilized in this study were simulated to validate the new approach. The results of unsteady-state WAG injection experiments performed at different conditions were used in this simulation study. The simulation of the WAG injection experiments confirmed the positive impact of updating the three-phase relative-permeability hysteresis parameters in the later WAG injection cycles. This change significantly improved the match between simulation and WAG experimental results. Therefore, a systematic workflow for acquiring and analyzing the relevant data to generate the input parameters required for WAG injection simulation is presented. In addition, a logical procedure is suggested to update the simulation model after the third injection cycle as a workaround to overcome the limitation in the current commercial simulators. This guideline can be incorporated in the numerical simulators to improve the accuracy of oil recovery prediction by any cycle-dependent three-phase process using the current simulation capabilities.

Injection of chemicals into sandstones could lead to wettability alteration, where oil characteristics such as the TAN (Total Acid Number) may determine the wetting-state of the reservoir. By combining the spontaneous imbibition principle (Amott-Harvey method) and interfacial tension indexers’ evaluations, we propose a workflow and a comprehensive assessment to evaluate wettability alteration and IFT when injecting chemical EOR agents. The study focused on examining the effect of alkaline and polymer solutions (alone) and alkali-polymer. The evaluation focused on comparing the effects of chemical agent injection on wettability and IFT due to: core ageing (non-aged, water-wet and aged, neutral to oil-wet); brine composition (no divalent and with divalent ions); core mineralogy (~2.5% and ~10% Clay) and crude-oil type (Low and high TAN). Amott experiments were performed on cleaned water-wet core plugs as well as on samples with restored oil-wet state. IFT experiments were compared for a duration of 300 minutes. Data was gathered from 48 Amott imbibition experiments with duplicates. IFT and baselines were defined in each case for brine, polymer and alkali on every set of experiments. When focusing on the TAN and aging effects it was observed that in all cases, the early time production is slower and final oil recovery is larger comparing to non-aged core plugs. This data confirms the change of rock surface wettability towards more oil-wet state after ageing and reverse wettability alteration due to chemical injection. Furthermore, application of alkali with high-TAN oil resulted in a low equilibrium IFT. In contrast, alkali alone fails to mobilize trapped low-TAN oil, but causes wettability alteration and neutral-wet state of the aged core plugs. Looking into brine composition, the presence of divalent ions promotes water-wetness of the non- aged core plugs and oil-wetness of the aged core plugs. Divalent ions act as bridges between mineral surface and polar compound of the in-situ created surfactant, hence accelerating wettability alteration. Finally, concerning mineralogy effects, high clay content core plugs are more oil-wet even without ageing. After ageing, a strongly oil-wet behaviour is exhibited. Alkali-polymer is efficient in wettability alteration of oil-wet core plugs towards water-wet state. Three main points are addressed in the paper: A comprehensive methodology to evaluate wettability and IFT changes for different oil and mineralogy types is presented In particular, for alkali injection, substantial wettability change effects are observed. For high TAN number oils, wettability and IFT effects can be quantified using the methodology and applied for screening of chemical agents for various rock types.

The decision analysis process to develop a petroleum field can be very complex. This process contemplates a set of tasks, which include the study of various representative scenarios, and different production strategies that aid decision-making. However, when it comes to giant reservoirs, the computational requirements of the respective simulation models may be too high. High computational cost may demand simplification that may yield suboptimal solutions so it is desirable to find simplifications that preserve the quality of the solutions. One approach to reduce the simulation requirements is to divide the reservoir into sectors, and to use sector models isolated in the decision making process. This study evaluates the feasibility of using a model of an isolated sector from a giant reservoir in the management of this sector. The observed decrease in the simulation time of the isolated model makes this methodology attractive. However, it is necessary to evaluate in advance the impacts of its use on the flow behavior of this sector when inserted in the Full Field model. The case study presented is a deterministic realization of a reservoir with analogous characteristics to the Mero pre-salt field, with high communication along the reservoir. The global differences found between the isolated model and the Full Field model presented a range that justifies the use of the isolated model in the development process of this sector, without losing significant accuracy in the results. A methodology is proposed to evaluate the differences between both models using field and well indicators. Discussions about the impact of local differences between the two models are presented. The causes of these differences were investigated and attributed to three main factors: the production strategy; changing of boundary conditions; and rock properties of the model.

Water flooding has been applied either along with primary production to maintain reservoir pressure or later to displace the oil in conventional and heavy oil reservoirs. Although it is generally accepted that water flooding of light oil reservoirs in oil-wet systems delivers the least oil compared to either water-wet or intermediate-wet systems, there is a lack of systematic research to study water flooding of heavy oils in oil-wet reservoirs. This research gives some new insights on the effect of injection velocity and oil viscosity on water flooding of oil-wet reservoirs. Seven different oils with a broad range of viscosity ranging from 1 to 15,000 mPa.s at 25 °C were used in fifteen core flooding experiments where injection velocity was varied from 0.7 to 24.3 ft/D (2.5 × 10 −6 m/s to 86.0 × 10 −6 m/s). Oil-wet sand (with contact angle of 159.31 ± 3.06°) was used in all the flooding experiments. Breakthrough time was precisely determined using an in-line densitometer installed downstream of the core. Our observations suggest that drainage displacement does not occur unless non-wetting (water) phase pressure exceeds a critical breakthrough capillary pressure. At the same injection velocity, this non-wetting phase invading pressure is a function of the viscosity of the oil being displaced. For the same viscosity ratio, oil recovery monotonically increases with increasing injection velocity suggesting that the flow regime is viscous-dominant for all the viscosities studied. This is consistent with the classical literature on carbonates ( deZabala and Kamath, 1995 ). However, the current work extends the classical learnings to a much wider operational envelope on oil-wet sandstones. In this paper, it is demonstrated that in an oil-wet system increasing velocity improves forced drainage to the extent that it takes over viscous fingering. For the viscous oil system (15,000 mPa.s), it was found that wettability critically affects the pressure gradient across the core to the extent that one order of magnitude larger pressure gradient was observed in an oil-wet system compared to the completely same system but water-wet. This notable larger pressure gradient in oil-wet system accompanies with delayed water breakthrough leading to incremental (around 30 % OOIP) oil recovery compared to the water-wet case. This is completely opposite to the classical literature on light oils and needs to be further investigated due to the lack of literature on heavy oil domains. Observations reported in this study can provide some useful information about the sizes of the pores being invaded as a function of oil viscosity and wettability, which is a subject of our future microfluidic studies at the pore scale.

Enhanced oil recovery (EOR) techniques often involve delivering chemicals, macromolecules, or particles in oil reservoirs to improve oil mobility and production. The harsh environment typical to the reservoir poses a great challenge to maintaining long-term stability of these agents. Moreover, accessing constricted regions in the reservoir with extremely tight pores and pore throats, and where large volumes of resources exist, require more efficient delivery methods than diffusion. We have developed an in-house EOR nano-agent (NanoSurfactant) platform using the inexpensive and abundant petroleum sulfonate salt surfactant. NanoSurfactants are chemically and colloidally stable at high salinity (> 56K ppm) and high temperature (> 90°C) conditions. Their structure, size, and surface properties suggest different transport mechanisms for enhanced delivery in oil reservoirs compared to conventional surfactants. We seek to improve the delivery of NanoSurfactants to regions in the reservoir that are inaccessible to conventional waterflood. Here, we explore diffusiophoresis (DP) as a mean to efficiently deliver NanoSurfactants to flow-restricted regions. Direct microscopic visualization experiments are conducted to study the migration of NanoSurfactants in different chemical gradients. These transient gradients are established in microfluidic channels mimicking dead-end pores in the reservoir. In addition, we study the effect of adding dilute macromolecules to the NanoSurfactant solutions on their DP migration. NanoSurfactants are labeled with a fluorescent dye to enable microscopic visualization and quantification of DP migration. Results showed that salinity gradients yield faster and deeper delivery of NanoSurfactants into the dead-end channels compared to diffusion without any gradients. A more pronounced migration is observed when small concentrations of macromolecules are added. Our findings expand the understanding of DP migration in an extremely high salinity environment. In addition, they provide insights into the utilization of natural or induced gradients in oil reservoirs to harness the DP migration for EOR applications.

A laboratory investigation was carried out to experimentally determine the extent of the salt precipitation effects on the petrophysical properties of deep saline aquifer during CO 2 storage. This was performed on selected core samples using laboratory core flooding process. The petrophysical properties (Porosity, Permeability) of the core sample were measured before core flooding using Helium Porosimetry and Scanning Electron Microscopy (SEM) to determine the morphology of the core samples. The core samples were saturated with brines of different salinities (5, 15, 25, wt% NaCl) and core flooding process was conducted at a simulated reservoir pressure of 1,000 psig, temperature of 45°C, with varying injection rates of 1.0, 1.5, 2.0, 2.5 and 3.0 ml/min respectively. The obtained results indicated that the porosity and permeability decreased drastically as salinities increases, noticeably because the higher concentration of brine resulted in higher amounts of salt precipitation. Porosity reduction ranged between 0.75% to 6% with increasing brine salinity while permeability impairment ranged from 10% to 70% of the original permeability. The SEM images of the core samples after the flooding showed that salt precipitation not only plugged the pore spaces of the core matrix but also showed significant precipitation around the rock grains thereby showing an aggregation of the salts. This clearly proved that the reduction in the capacity of the rock is associated with salt precipitation in the pore spaces as well as the pore throats. Higher injection rates induced higher salt precipitation which caused reduction in porosity and permeability. This is attributed to the fact that; the higher injection of CO 2 vaporizes the formation brine more significantly and thereby increasing brine concentration by removing the water content and enhancing precipitation of salt. These findings provide meaningful understanding and evaluation of the extent of salt precipitation on CO 2 injectivity in saline reservoirs. The insight gained could be useful in simulation models to design better injectivity scenarios and mitigation techniques

During the implementation of microbial enhanced oil recovery (MEOR) technique in reservoirs, various reservoir and microbial kinetic parameters play major roles in governing the efficiency of crude oil recovery from hydrocarbon reservoirs. The present study numerically investigates the sensitivity of reservoir porosity, injected microbial species at different temperatures, maximum microbial specific growth rate, Monod saturation constant and yield coefficient on biomass and biosurfactant production and their impacts on microscopic oil displacement efficiency within the reservoir. A black-oil biochemical multi-species reactive transport model in porous media is developed by coupling the kinetic model with the corresponding transport model. The governing equations involve coupled transport of nutrients and microbes by dispersion and convection, growth and decay rates of microbes, chemotaxis, nutrient consumption, and deposition of microbes and nutrients on rock-grain surfaces. Coupled empirical equations are used to estimate biosurfactant production, oil-water interfacial tension reduction, change in viscosity of injection fluid and their impacts on oil mobility and decrease in residual oil saturation within reservoir. Finite difference discretization technique is adopted to solve the governing equations. Results of the present model are found to be numerically stable and match very well, when verified, with the previously published analytical and experimental results. The model results suggest that at very low reservoir porosity (less than 20%), an early breakthrough of nutrients, microbe and biosurfactant leave insignificant concentrations in their respective fronts which are insufficient for the recovery of the trapped oil. Also, increase in porosity beyond 20% causes loss of nutrients, microbes and biosurfactant because they undergo higher dispersion during their transport within reservoir. Further it is observed that the nature of microbes and nutrients used for MEOR application affect biosurfactant production and in turn oil recovery to a large extent. Those microbial species having very less Monod saturation constant values have high affinity towards their substrates. This phenomenon drastically increases the rates of nutrient consumption and production of biomass and biosurfactant within reservoir when suitable substrate compounds are used, irrespective of differences in the yield coefficients of the microbes. The optimized reservoir and microbial kinetic properties increase capillary number above 10 −3 which further increases oil mobility towards production well and there is a significant decline in the effective residual oil saturation (less than 5%) within the reservoir. The present study provides an improved understanding of the combined effects of reservoir porosity and microbial kinetic parameters on fundamental MEOR processes which will better characterize the suitability of a MEOR technique in a typical petroleum reservoir. Moreover, the developed numerical model is easier to implement and produces faster results with relatively lower computational cost which helps in making quick decision before applying MEOR processes in the field.