Streamline Simulation Research Articles

Optimizing Water-Cut and Boosting Oil Recovery: Geological Insights from Mishrif Reservoir, Buzurgan Oil Field

This study utilizes streamline simulation to model fluid flow in the complex subsurface environment of the Mishrif reservoir in Iraq's Buzurgan oil field. The reservoir faces challenges from high-pressure depletion and a substantial increase in water cut during production, prompting the need for innovative reservoir management. The primary focus is on optimizing water injection procedures to reduce water cuts and enhance overall reservoir performance. Three waterflooding tactics were examined: normal conditions without injectors or producers, normal conditions with 30 injectors and 80 producers and streamline simulation using the frontsim simulator. Three main strategies were employed to streamline water injection in targeted areas. Over a 22-year forecasting period and employing seven Strategies, streamline simulation were optimized both oil and water outputs. The hybrid Strategy-7 as mixed between all three outperformed Strategy-1 that was gave highest optimization result for only one strategy, yielding the highest cumulative oil production of 1281 million stock tank barrels, the highest oil recovery factor of 24.1%, and a minimal of 2.5% water cut. This study underscores the importance of streamline simulation in managing reservoirs under challenging subsurface conditions, highlighting that a thoughtful integration of streamlining tactics can significantly improve reservoir performance even enhancing oil recovery and addressing water-related issues. The findings contribute valuable insights for optimizing waterflooding strategies in similar globally geological contexts.

Predicting fluid flow in reservoirs: analysis of fracture clustering in outcrop analogues

Researchers have used lacunarity, a parameter that quantifies scale-dependent clustering in patterns, to differentiate fracture networks that belong to the same fractal system. In a previous study, the authors showed that lacunarity is efficient in representing connectivity and fluid flow in fractal-fracture models with the same fractal dimension. The objective of this research is to investigate if the concepts thus developed are applicable to outcrop analogues that are representative of subsurface fractured reservoirs. A set of nested fracture networks belonging to a single fractal system but mapped at different scales and resolutions is considered in this study. Lacunarity and connectivity values of these maps are evaluated using geospatial data analysis techniques. Fracture continuum (FC) models are built from these fracture maps and a streamline simulator, TRACE3D, is used to flow simulate these maps. Results show that although the fractal dimension of these maps is same, differences exist in the values of lacunarity, percolation connectivity and also fluid recovery values. It is further noted that the clustering, connectivity and fluid recovery values can be pairwise correlated very well for these natural fracture maps. Thus, the overall results indicate that connectivity in fracture maps, and hence their flow properties, are controlled by lacunarity or scale-dependent clustering attributes. Therefore, there could be novel applicability of the lacunarity parameter in calibrating discrete fracture network (DFN) models with respect to connectivity in natural fracture maps and the prediction of flow behaviour in fractured reservoirs. Thematic collection: This article is part of the Digitally enabled geoscience workflows: unlocking the power of our data collection available at: https://www.lyellcollection.org/topic/collections/digitally-enabled-geoscience-workflows

Prediction of thermal front movement in geothermal reservoirs containing distributed natural fractures

When designing a reinjection scheme for geothermal development, one needs to predict the flow and thermal behavior between the recharge and discharge wells. Premature thermal front breakthrough is of great concern and is often observed in real fields. However, prediction methods based on homogeneous media are prone to overly optimistic estimates. In this study, geothermal reservoirs with vertical fractures which are discretely distributed in the permeable rock are considered, and the streamline simulation is developed and applied to evaluate the thermal front movement, represented by the characteristic times tD*. With 1000 simulation results for stochastically generated natural fracture systems, regression models are developed for the expected values of tD* with minimal information requirements on fracture parameters. In general, the fracture orientation θf has a stronger negative correlation with tD* than the total fracture length Σf. The intensity of natural fractures has opposing effects (delay or advance) on tD* depending on θf, and taking this effect into account improves the quality of the regression model. In addition, when the pressure difference between the doublet wells is available, the model accuracy is further improved by incorporating pressure data into the regression. The prediction models are of practical use for understanding the thermal behavior and designing a reinjection scheme in fractured geothermal reservoirs.

A novel streamline simulation method for fractured reservoirs with full-tensor permeability

In this work, we develop a novel streamline (SL) simulation method that integrates seamlessly within the embedded discrete fracture model (EDFM). The novel SL-based method is developed based on a hybrid of two-point flux approximation (TPFA) and mimetic finite difference (MFD) methods, which is applicable to a two-phase anisotropic flow in fractured reservoirs. We refer to this novel approach as EDFM-TPFA-MFD-SL. The approach is operated in an IMplicit Pressure Explicit Saturation (IMPES) manner. First, this work establishes a novel EDFM utilizing a hybrid TPFA-MFD scheme to solve the pressure equation for phase flux approximation. Subsequently, we introduce a practical streamline tracing workflow designed to derive the distribution of streamlines within the reservoir domain and the time-of-flight distribution along each individual streamline. This feature allows for the parallel computation of water saturation along the streamlines. Two numerical examples are presented to validate the superiority of the proposed EDFM-TPFA-MFD-SL method compared to the existing streamline-based EDFM on cases with full-tensor permeability. The results show that the proposed method could significantly mitigate the numerical dissipation and reduce the computation costs. Another numerical example demonstrates the effectiveness of the proposed method in dealing with complex fracture networks and providing rapid flow diagnostics, indicating its significant potential for real-world field applications.

A new two-step particle tracking and channels model method for preferential 3-D flow and transport in large DFNs of fractured aquifers

A new two-step method has been developed for predicting three-dimensional (3-D) pollutant plumes and breakthrough curves (BTC) in fractured aquifers. Predicting fluid motion fields and pollutant concentrations in groundwater is a challenging task, due to the difficulties in building a 3-D discrete fracture network (DFN) with the same geometry of fractures and interconnections as in the studied aquifer and the computational complexity of the problem being modeled. To improve the representation of DFN, geological characterization of fracture apertures was performed using field well-pumping data as the prerequisite for the modeling approach. The modeling was performed in two steps: first, 3-D particle tracking following streamline (PTFS) simulations in DFN backbones, and second, a 3-D channels model (CM) analytical solution. The PTFS simulations captured the mean properties of the 3-D velocity field relevant to spatial and temporal transport along preferential flow pathways of a fractured aquifer. The 3-D CM solution yielded the exact BTC of concentrations accounting for the slowest flow pathways typically excluded from DFN backbones extraction methods. The PTFS/CM simulations were initially performed at the lab scale on a 3-D 20 m rock block from the Bari (South Italy) fractured aquifer. Results were consistent with the chlorophyll-A BTC obtained from a well-to-well tracer experiment. Subsequently, the capability of the new method was tested by increasing the scale of simulations to a larger 3-D DFN of 200 m with 2,200 fractures. The resultant BTC was obtained in 32 min, showing the proposed PTFS/CM technique can rapidly determine complex 3-D solutions in heterogeneous fracture-dominated aquifers. The applied Lagrangian and Eulerian techniques can provide quasi-deterministic BTCs and 3-D maps of pollutant concentrations, avoiding extensive computations required for conforming mesh methods. Moreover, the solution does not require multiple randomly arranged DFN realizations, as in particle tracking-based stochastic methods. These results have significant implications in modeling transport at the aquifer scale, where DFNs are composed of thousands of fractures.

Characterizing fractured reservoirs by integrating outcrop analogue studies with flow simulations

This research focuses on how ‘static’ properties of fracture networks can be studied by considering ‘dynamic’ flow simulation, while static properties such as clustering, connectivity, variation in aperture and, of course, anisotropy of fracture networks can be quantified using different geostatistical/data analysis techniques. The flow responses through such networks can be simulated to check if flow simulation can be used as a tool for evaluating its geometry. In order to achieve this, outcrop analogues of fractured reservoirs are converted into permeability structured grids implementing the fracture continuum (FC) concept. These FC models are flow simulated in a streamline simulator, TRACE3D. Results of the first experiment show that rather than the ‘fractal dimension’, the ‘lacunarity parameter’, which quantifies scale-dependent clustering of fractures, is a unique identifier of network geometry and acts as a proxy for fracture connectivity and an indicator of flow behaviour. The FC model further accommodates variability in fracture apertures and, thus, in a second experiment a set of models with a hierarchical aperture distribution was built and tested for their time-of-flight (TOF) and recovery curves, which showed that smaller fractures with narrow apertures do not significantly contribute to flow. In a third experiment considering anisotropy, it was observed that tightly clustered fractures along preferential directions can be identified from anisotropy in flow patterns. The results from these three experiments show that flow patterns in fracture networks can indicate the overall scale-dependent clustering, the anisotropy that arises from such clustering and that narrower fractures do not significantly alter the overall flow behaviour. Thematic collection: This article is part of the Digitally enabled geoscience workflows: unlocking the power of our data collection available at: https://www.lyellcollection.org/topic/collections/digitally-enabled-geoscience-workflows

The performance of streamline simulation technique to mimic the waterflooding management process in oil reservoirs

Multiple simulation techniques are often used to predict the performance of waterflooding and to plan the infill drilling techniques via a process called waterflooding management. However, such simulation techniques usually suffer from many drawbacks and shortages. Therefore, the waterflooding process management is in an evitable need for a robust technique, which can predict the optimal water injection rates and the incremental oil production in a cost-effective manner.In this study, the streamline simulation technique (SST) was used to visualize and analyze the fluid flow patterns in order to investigate the validity of this technique for improving waterflooding management process. In addition, the feasibility of SST in waterflooding management was clearly tested by setting new injection strategies to improve the sweep efficiency via estimating the injector-producer relationship as well as the water injection efficiency. Furthermore, the advantages of streamline simulation visualization in determining the best infill drilling locations, which production wells could be converted to injection wells, and optimizing water injection rates based on monitoring and trials were investigated. The results of this research indicated that the streamline simulation technique is capable to efficiently model and predict the waterflooding process. The SST is computationally efficient and fast in terms of providing flow visualization among injectors and producers, estimating an allocation factor for injection system, and optimizing the locations of new injectors/producers’ wells to increase the sweep efficiency. In addition, the SST could provide a deep understanding with visualization to the waterflooding process and how to improve the waterflooding in oil reservoirs. In this work, through the comparison of various waterflooding scenarios, we discovered the best solution that eliminated the need for optimization algorithms with high computational requirements. This approach relies on areas exhibiting low streamline densities to enable streamlined prediction of infill well locations, thereby reducing simulator processing time. Consequently, this method represents an effective first step in the process of identifying approximate infill well locations, and its efficacy can be enhanced by integrating optimization methods.

Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm

Well production optimization is a complex and time-consuming task in the oilfield development. The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production. This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency. To improve optimization efficiency, a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization (BADS) algorithm is established. This new objective function, which represents the water flooding potential, is extracted from streamline features. It only needs to call the streamline simulator to run one time step, instead of calling the simulator to calculate the target value at the end of development, which greatly reduces the running time of the simulator. Then the well production optimization model is established and solved by the BADS algorithm. The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples. Results demonstrate that the new objective function is positively correlated with the cumulative oil production. And the BADS algorithm is superior to other common algorithms in convergence speed, solution stability and optimization accuracy. Besides, this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods. It can provide a more effective basis for determining the optimal well production for actual oilfield development.

3D numerical modelling and simulation of the impact of fault zones on fluid flow in sandstones of the Rio do Peixe Basin, NE Brazil

Deformation bands are usually responsible for a reduction in permeability perpendicular to the structure planes of up to three orders of magnitude, while the fault core represent a reduction of up to seven orders of magnitude in cross-fault permeability, imposing large anisotropies to fluid flow. As deformation bands occur distributed along the damage zone, they impact not only the across-fault flow but also the along-fault flow. The fault core is usually represented using fault-transmissibility multipliers (TMs) along the fault planes, using well-established workflows. However, there is a lack of methods to represent fault damage zones in any direction and grid-cell sizes. In this context, we proposed new methods to: (1) estimate the deformation intensity in damage zones; (2) calculate their most representative value within the cell domain; and (3) calculate the equivalent permeability of a cell containing oblique deformation bands. The workflow is applied to a 3D numerical model for the Santa Helena High in the Rio do Peixe Basin, NE Brazil. We performed streamline simulations in four models to evaluate the impact of fault damage zones and the fault core in fluid flow. Our models show that the fault core and damage zone negatively affected the performance of the reservoir. Supplementary material : A description of the method developed to estimate the deformation intensity in damage zones and of the method developed to calculate the equivalent permeability are available at https://doi.org/10.6084/m9.figshare.c.6251469

Challenges and Opportunities in Oil Rim Reservoir Development

Low oil recovery is one of the common problems in the field development of thin oil rims associated with gas-condensate. The fast gas and water conning of the reservoirs are the main causes of sharp oil rate decline and low cumulative oil production per well. Low recovery efficiency is related to the oil saturated thickness and if oil saturation is less than 10 m, most of oil volumes in place are moved to transition zones. 3D numerical and streamline simulations are performed for the development of thin oil rims of one of the pay zones in Bokabil Formation of Haripur gas field. The development option with four vertical oil production wells and nine water injection wells has been proposed to cover the entire reservoir with the efficient sweeping. The simulation study of the dynamic model has revealed that vertical wells through the reservoir are able to make a short drainage path and produce insignificant quantity of oil and the production period is terminated shortly. As an alternative development option a rim shaped production well and a rim shaped water injection well is designed. The development option with a rim shaped production and an injection wells covers large drainage length and produce significant amount of oil. This option is technically and economically feasible. The Dhaka University Journal of Earth and Environmental Sciences, Centennial Special Volume June 2022: 85-88

A comprehensive performance evaluation methodology for miscible gas flooding: A case study in a giant carbonate reservoir in Middle East

This work focuses on a typical low-permeability carbonate reservoir in Middle East that has been developed by miscible hydrocarbon (HC) gas flooding for more than 10 years. The oilfield is now suffering from gas channeling, high gas/oil ratio (GOR), and invalid gas circulation. To figure out the reasons and propose an optimized development plan, it is necessary to accurately determine the characteristics and behavior of miscible gas flooding. To achieve this, a comprehensive performance evaluation method for miscible gas flooding is established in this work by integrating production data, inter-well gas tracer test, saturation surveillance, pressure surveillance, minimum miscibility pressure (MMP) variation, and streamline simulation. The following miscible HC gas flooding characteristics are interpreted, including typical gas flow path, miscibility behavior, major controlling factors impacting performance, and the main challenges of the current development scheme, which provides a fundament for proposing mitigation plan. By using this evaluation method, the behavior of gas flow in the ongoing miscible flooding process is precisely characterized, which is a “gravity override-gas coning” mode in which gas override is formed by an upward injected gas flow and then gas flows through gas cap to producers that leads to gas coning, resulting in high GOR and invalid gas circulation. This flow mode mainly resulted from the unsatisfied miscibility that led to gas escaping from miscible phase and gas channeling. Furthermore, it was found out that pressure difference is the dominating factor for gas channeling. In addition, we also found that MMP varies during HC gas injection process due to the change in the oil composition, which emphasizes the importance of recovering and maintaining pressure. Based on these findings obtained from extensive dynamic performance analysis and numerical simulations, an optimization strategy is finally proposed for improving the performance of miscible HC gas flooding.

Flow field characterization and evaluation method based on unsupervised machine learning

Long-term water flooding can be inefficient due to imbalanced displacement, resulting in sub-optimal recoveries. Therefore, the quantitative characterization and evaluation method of the flow field is significant for further development and adjustment. In this study, based on streamline simulation results, decoding rules were formulated to extract streamline data. Considering the attribute feature of each node along the streamline, flow field characterization indices were constructed. And combining the fast density peaks clustering (FDPC) algorithm and silhouette coefficient (SC), a novel flow field evaluation method based on streamline clustering was proposed. Results indicated that the invalid water circulation channels and areas with developing potential in reservoirs can be identified. Besides, the distribution of flow field can also be observed, and the characteristics of the identified region can be analyzed, which provides a basis for the subsequent flow field adjustment. Meanwhile, streamlines between injection and production wells can be subdivided to describe the distribution of water displacement capacity. Based on the evaluation results of streamline clustering, Gudao oilfield adjusted the flow field through injection-production adjustment, which effectively improved the development effect of the block and increased the recovery degree from 50.3% to 52.4%. This work provides an effective evaluation method to directly characterize the displacement changes for underground flow field, and it is of great significance for the decision-making of water flooding structure adjustment and optimization.

Flow Field Description and Simplification Based on Principal Component Analysis Downscaling and Clustering Algorithms

The flow field obtained from streamline simulation reflects key properties of the reservoir, such as the distribution of the remaining oil and the location of channels. However, in the three-dimensional streamline field, the advantages of streamline simulation are limited. Because numerous streamlines interfere with each other and distribute in a sophisticated way, it is really difficult to infer the connectivity between wells and the flow characteristics of the reservoir. To make a more effective and visualizable description of the flow field, the three-dimensional streamline field has to be simplified. In this paper, principal component analysis (PCA) is applied to parameterize the streamline attributes and reduce the dimensionality of the flow field. After dimension reduction, the principal components of the streamline field can be analyzed by the clustering method. In the clustering procedure, the mainstream lines are selected according to the clustering center, thereby intuitively illustrating the properties of the reservoir. Through experimental verification, the proposed method can characterize the streamlines of the flow field more efficiently and reflect the inter-well connectivity more clearly than the commercial numerical simulator.

Worksheet Screening Of Co2 Eor Sequestration Potential In Indonesia

CO2 injection into subsurface with the purpose to increase incremental oil production had been popularized in 1970s in US. Nowadays, this type of EOR methods not only offers more oil but also utilizing reservoir as CO2 storage in the context of CO2 emission abatement. The objective of this research is to produce simple and efficient worksheet on EXCEL base in order to asses and screen out quickly the potential of implementation of CO2 EOR sequestration in depleted oil fields in Indonesia.Key elements of this worksheet comprise engineering aspect and economical aspect. A sequence workflow of technical performance of CO2 flooding was done using streamline simulator in which outstanding output from simulator needs robust data preparation and cautious parameter set up. For the case studied here, total incremental oil recovery at the end of the project is 4.52% from original oil in place (IOIP) or about 6.23 MMSTB. “Prophet” was used to simulate CO2 sequestration during CO2 EOR incorporating residual trapping. The amount of CO2 trapped in reservoir was acquired by subtracting the total injected CO2 with CO2 produced. The total capital expenditure for sequestration CO2 EOR studied here is estimated $48.3 MM. It is expected that $16.5 MM will be placed in service by 1st year with the remaining $31.7 MM to be placed in service by 2nd year. Annual average operating cost was estimated to be $5.4 MM. As for fiscal terms, the following assumptions have been incorporated into the economic evaluations: (1) FTP 10%, (2) Investment Credit 17%, (3) Contractor Oil Split 26.6018%, (4) Government Split 73.3982%, and (5) Tax 44%. The economic analyses were carried out based on the project life time 7 years and the sales of incremental oil amount 5.6 MMSTB with an assumption that price for oil was $68 per barrel based on monthly average OPEC Basket Price during April-09 until March-10. Economic results of the development with discount factor 7 percent as indicated has a Contractor DCF Rate of Return 53.3 percent, Contractor Net Present Value $31.3 MM, and revenue to the Government of Indonesia $188.2 MM. With this economic indicator, the project of Sequestration CO2 EOR is economically feasible. The developed worksheet enables to do quick judgment on the viability a CO2 EOR sequestration project hence make it easier to someone who wants to screen out a large number of reservoirs rather than using detailed numerical simulator. It will much more saved time and decrease works intensity.

Evaluating Flow in Fractal-Fracture Networks: Effect of Variable Aperture

Abstract. While fractal models are often employed for describing the geometry of fracture networks, a constant aperture is mostly assigned to all the fractures when such models are flow simulated. In nature however, almost all fracture networks exhibit variable aperture values and it is this fracture aperture that controls the conductivity of individual fractures as described by the well-known cubic-law. It would therefore be of practical interest to investigate flow patterns in a fractal-fracture network where the apertures scale in accordance to their position in the hierarchy of the fractal. A set of synthetic fractal-fracture networks and two well-connected natural fracture maps that belong to the same fractal system are used for this purpose. A set of dominant sub-networks are generated from a given fractal-fracture map by systematically removing the smaller fracture segments with narrow apertures. The connectivity values of the fractal-fracture networks and their respective dominant sub-networks are then computed. Although a large number of fractures with smaller aperture are eliminated, no significant decrease is seen in the connectivity of the dominant sub-networks. A streamline simulator based on Darcy's law is used for flow simulating the fracture networks, which are conceptualized as two-dimensional fracture continuum models. A single high porosity value is assigned to all the fractures. The permeability assigned to fractures within the continuum model is based on their aperture values and there is nearly no matrix porosity and permeability. The recovery profiles and time-of-flight plots for each network and its dominant sub-networks at different time steps are compared. The results from both the synthetic networks and the natural data show that there is no significant decrease in fluid recovery in the dominant sub-networks compared to their respective parent fractal-fracture networks. It may therefore be concluded that in the case of such hierarchical fractal-fracture systems with scaled aperture, the smaller fractures do not significantly contribute to connectivity or fluid flow. In terms of decision making, this result will aid geoscientists and engineers in identifying only those fractures that ultimately matter in evaluating the flow recovery, thus building models that are computationally less expensive while being geologically realistic.

Fast Optimization of Injector Selection for Waterflood, CO2-EOR and Storage Using an Innovative Machine Learning Framework

Optimal injector selection is a key oilfield development endeavor that can be computationally costly. Methods proposed in the literature to reduce the number of function evaluations are often designed for pattern level analysis and do not scale easily to full field analysis. These methods are rarely applied to both water and miscible gas floods with carbon storage objectives; reservoir management decision making under geological uncertainty is also relatively underexplored. In this work, several innovations are proposed to efficiently determine the optimal injector location under geological uncertainty. A geomodel ensemble is prepared in order to capture the range of geological uncertainty. In these models, the reservoir is divided into multiple well regions that are delineated through spatial clustering. Streamline simulation results are used to train a meta-learner proxy. A posterior sampling algorithm evaluates injector locations across multiple geological realizations. The proposed methodology was applied to a producing field in Asia. The proxy predicted optimal injector locations for water and CO2 EOR and storage floods within several seconds (94–98% R2 scores). Blind tests with geomodels not used in training yielded accuracies greater than 90% (R2 scores). Posterior sampling selected optimal injection locations within minutes compared to hours using numerical simulation. This methodology enabled the rapid evaluation of injector well location for a variety of flood projects. This will aid reservoir managers to rapidly make field development decisions for field scale injection and storage projects under geological uncertainty.

Improving Water Flooding Management through Facies Remodeling and the Use of Streamlines and Finite Difference Simulators

A successful water flooding project requires continuous surveillance and updated studies. The use of modern tools and practices is also essential to achieve maximum oil recovery. Field ‘X’ lies in the Western Desert of Egypt. Although the field employs water flooding as a secondary recovery mechanism, it suffers from low oil recovery, low sweep efficiency and high water’s production rates. In 2014, a field development plan was issued with a target recovery factor of 30% using water flooding. However, actual production has significantly underperformed initial forecasts, motivating a re-evaluation of the old plan. In particular, it was considered necessary to revisit the underlying geologic concept and how this was incorporated into flow simulation forecasts. The aim was to maximize the oil recovery factor before resorting to an expensive tertiary recovery plan; especially, under current low oil prices. This paper discusses the value of updating both static and dynamic models to better incorporate uncertainty associated with facies distribution. It also demonstrates the use of streamline simulation to reallocate water injection rates and determining the role of facies communication in improving the areal sweep efficiency. The new injection scheme is supported by the updated dynamic modelling study and added an incremental reserve of 6.5% and unlocked 28% of the oil in place in the field. Keywords: Water-flooding; Facies; Streamline; Simulation

Benefits of the Tracers Test Technique in Improving the Performance of Group Wells

This study aims to determine the benefits of the interwell tracer test technique in improving the streamline simulation on the existing array's re-look. It also analyses the best scheme for the injection spot to enhance oil recovery. This study's subject parameters are limited to the tracer's breakthrough time, produced concentration, cumulative production, and pathline movement. The results showed that previous studies distinguished the correlation between injectors and producers with the development of a new pathline that conveys a scheme of water-flood for the application. Furthermore, several developments of water-flood schemes have been executed for better oil recovery in the mature fields worldwide. The vigorous simulation model is an effort to imitate the actual field capable of enhancing the character's understanding and helping the waterflood to rinse the oil trap or the unswept pocket. Unlike a Cartesian model, the streamline conveys an enhanced portrait of the transmissibility reservoir in terms of pressure-driven. The streamline model suggests the injector's preferred position to unlock any unswept oil in the formation and minimize the water path conflict, which leads to over injection in some regions. The expected outcome is the ultimate oil increment with the original technique associated with re-patterning the wells appropriately to gain residual oil saturation in the virgin alleyway.

An efficient method for injection well location optimization using Fast Marching Method

Well placement is one of the challenging steps in field development optimization. Finding optimal locations with fewer function evaluations and less time is crucial when dealing with giant models. In this study, we propose a method based on the combination of Fast Marching Method and Particle Swarm Optimization to decrease the number of function evaluations in optimizing the location of vertical injection wells. The idea is to restrict the optimization algorithm's search space to a region around the drainage boundary of producers. Thereby, the optimization algorithm can find good locations with fewer function evaluations compared to direct optimization. Drainage boundaries are predicted based on the diffusive time of flight (arrival time) calculated by the Fast Marching Method. First, the performance of the proposed method in predicting the drainage boundaries is evaluated by verifying the drainage boundary of four producers on two synthetic models using the fast marching method and streamline simulator which showed a good match. Next, the approach is applied to two- and three-dimensional example cases, including four synthetic models and a real field case to test the robustness and efficiency of the proposed method. Results are compared with the direct optimization approach and showed that the proposed approach can provide higher Net Present Values with fewer function evaluations most of the time. Finally, a comparison between the computational efficiency of the fast marching method and streamline simulator showed that the time needed by the fast marching method to predict the drainage boundary of the wells was orders of magnitude lower than the streamline simulator. • PSO-FMM is used to facilitate the process of finding good positions for injection wells. • PSO-FMM could find appropriate locations for the injectors with fewer function evaluations compared to direct optimization. • FMM could predict the drainage boundary of producers with satisfactory accuracy compared to streamline simulation. • Computational time required by FMM to estimate the drainage boundary was much lower than streamline simulation.

High-order streamline simulation and macro-scale visualization experimental studies on waterflooding under given pressure boundaries

In this paper, a new high-order streamline simulation method with a known pressure boundary is proposed. It extends the Riemann approach along streamlines from constant flow rate boundaries to given pressure boundaries. This method computes the varied flow resistance of streamtube directly by using the velocity and time-of-flight of its central streamline, and improves the simulation accuracy by applying a high-order streamline tracing method. Simultaneously, a series of macro-model visualization experiments are performed to study waterflooding processes under given pressure boundaries. The new streamline method is independently validated by history matching and direct modelling of the experiments. Finally, the capillary effects at the water front are quantified as a function of time and space with the assists of streamline simulations.