Browsing by Subject "Reservoir engineering"

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Accounting for exterior flow using the modified logistic growth model for unconventional geopressured shale reservoirs
(2023-04-21) Villarroel Salvatierra, Julio Cesar; Lake, Larry W.
The flow of gas in shale gas wells is known to be linear from the matrix through fractures. At early times, the rate declines in proportion to the inverse of square root of time (t⁻¹/²). Once fractures start interfering each other, the rate from the stimulated reservoir volume (SRV) declines exponentially (Patzek et al, 2013). The scope of this work is to assess the flow beyond boundary-dominated flow. Defining the existence of “exterior flow” and further use of decline curve analysis in unconventional reservoirs. This regime is the linear flow of gas from the non-stimulated matrix “feeding into” the depleted stimulated reservoir volume, at late times, beyond boundary-dominated flow. Additionally, we present novel diagnostic plots on rate-time data to obtain the characteristic time of switching from boundary-dominated to exterior flow that enables the prediction of additional volumes produced under this new flow regime. These volumes could be justified as probable reserves (P2). Clark, et al. (2011) presented a decline curve model based on nature’s theory of logistic growth that enlightened the use of the carrying capacity parameter “K” as a proxy for the Estimated Ultimate Recovery (EUR). However, in geopressured shales such as the Haynesville Shale, where Arps (1945) or any of the decline curve models currently available may not fit production curves, a flow regime analysis is needed in order to characterize the entire well history data and fit a model. Since all decline curve models are empirical, after appropriate flow regime identification, the modified logistic growth model (m-LGM) provides some physical meaning about the EUR. The logistic growth model fits all periods in a typical shale gas well: ramp-up, plateau, sharp decline; and the period described as exterior flow, which is evident as a kink in the slope of the logarithm of rate vs. time plot, is characterized by using an exponential decline tail (b-factor = 0). Moreover, for all the wells observed, the characteristic time of switching from boundary-dominated to exterior flow is between 4.5-5.0 years independent of well completion schemes and/or location. When volumes obtained from exterior flow are forecasted to economic limit rate, an additional 10-20% is observed compared to the EUR forecasted using classic decline curve analysis. As the Pareto Principle states: 80% of production comes from the most important 20% of the resource (ideally, the depleted stimulated reservoir volume, in this case). Thus, the remaining 20% from exterior flow. This could be a significant volume if hundreds or thousands of wells are accounted for in the basin. Finally, we present new diagnostic plots using rate-time data to better understand the flow regimes existing in a geopressured shale production curve that enables estimates of the volumes beyond boundary-dominated flow. This method accounts for an additional recovery that could be justified and categorized as probable reserves
An integrated peridynamics-finite volume based multi-phase flow, geomechanics and hydraulic fracture model
(2019-12-16) Agrawal, Shivam; Sharma, Mukul M.; Foster, John T., Ph. D.; Olson, Jon E; Mohanty, Kishore; Ouchi, Hisanao
Hydraulic fracturing in unconventional reservoirs exhibits several interesting phenomena including the interaction of hydraulic fractures with multi-scale heterogeneities such as natural fractures, stress/barrier layers, bedding planes, shale laminations, and mineralogy. Moreover, hydraulic fractures originating from different clusters or stages in a multi-stage, multi-cluster treatment interact among themselves. Mathematical models, with various degrees of numerical complexity, are developed for gaining better insights into the physics governing these phenomena. Peridynamics-based hydraulic fracturing model developed by Ouchi (2016) has been demonstrated to capture all of these phenomena. However, its major drawback is that it is computationally expensive. In this dissertation, we have extended the capabilities of the model to multi-phase flow and made it significantly faster by coupling it with the less expensive Finite Volume Method. The single-phase peridynamics flow model for slightly compressible, Newtonian fluids has been generalized for multiphase, multicomponent flow of compressible, non-Newtonian fluids. The generalized flow model has been coupled with the fracturing model and compared with laboratory experiments performed under low confining stresses. The extended model is also applied to simulate the growth of fractures from a new (child) well in the presence of depleted regions created by production from the fractures of an old (parent) well under high confining stresses. The interaction of a hydraulic fracture (HF) with a natural fracture (NF) is investigated. Remote shear failure of the NF due to the pororelastic stress changes caused by the propagating HF are considered. Consistent with the experiments, the remote shear failure is shown to result in the bending of the HF towards the NF before intersecting with it. Accounting for the effects of remote shear failure and poroelasticity, numerical crossing criteria for the HF-NF interaction are developed. The hydraulic fracturing model based on peridynamics (PD) theory is coupled with the less expensive Finite Volume Method (FVM), following the PD-FEM coupling method proposed by Galvanetto et al. (2016). Significant improvements in computational performance are achieved by the coupled model relative to the pure PD-based model, without compromising the unique original capabilities. By monitoring material damage in remote heterogeneous regions, a workflow for estimating the extent of the Stimulated Reservoir Volume (SRV) around a primary hydraulic fracture is developed. A sensitivity study for the effects of elastic properties of the formation, injection rate, and the reservoir fluid type on SRV extent is presented
Analyzing databases using data analytics
(2015-12) Lee, Boum Hee; Lake, Larry W.; Mohanty, Kishore K
There are many public and private databases of oil field properties the analysis of which could lead to insights in several areas. The recent trend of Big Data has given rise to novel analytic methods to effectively handle multidimensional data, and to visualize them to discover new patterns. The main objective of this research is to apply some of the methods used in data analytics to datasets with reservoir data. Abstract Abstract Using a commercial reservoir properties database, we created and tested three data analytic models to predict ultimate oil and gas recovery efficiencies, using the following methods borrowed from data analytics: linear regression, linear regression with feature selection, and Bayesian network. We also adopted similarity ranking with principal component analysis to create a reservoir analog recommender system, which recognizes and ranks reservoir analogs from the database. Abstract Among the models designed to estimate recovery factors, the linear regression models created with variables selected with sequential feature selection method performed the best, showing strong positive correlations between actual and predicted values of reservoir recovery efficiencies. Compared to this model, Bayesian network model, and simple linear regression model performed poorly. Abstract For the reservoir analog recommender system, an arbitrary reservoir is selected, and different distance metrics were used to rank analog reservoirs. Because no one distance metric (and hence the given reservoir analog list) is superior to the other, the reservoirs given in the recommended list are compared along with the characteristics of distance metrics.
Application of a one dimensional nonlinear model to flow in hydrofractured shale gas wells using scaling solutions
(2015-05) Male, Frank Ryan; Marder, Michael P., 1960-; Patzek, Tadeusz W.; Swinney, Harry; Lake, Larry; Gordon, Vernita
Estimations of shale gas reserves rely heavily on decline analysis of existing wells. In this work, I describe a new method of production analysis for shale gas reservoirs using a minimal model. This method relies on formulating a universal production curve for wells in each shale gas field such that production from a hydrofractured shale gas well in a particular field is only distinguished from other wells by two scaling parameters: the time to boundary-dominated flow and the total hydrocarbon in place. This technique bridges the gap between the simple empirical models often used for decline analysis and the complex analysis offered through full 3-dimensional reservoir simulations. I provide production forecasts and estimated ultimate recoveries for wells in the Barnett, Fayetteville, Haynesville, and Marcellus shale gas plays, and propose an extension to the method to facilitate analysis of the Eagle Ford and Bakken shale oil plays. The simplicity and power of this method makes it ideal for performing decline analysis on large numbers of wells.
Applications for Response Surfaces in Reservoir Engineering
(1999-05) Narayanan, Keshav; White, Christopher D.
Pseudofunctions used in scaled up reservoir simulation models depend on the geology, recovery process and fluid velocities. Accurate pseudofunctions can be derived in every section of the reservoir model to be coarsened by expensive fine-scale simulations with appropriate boundary conditions. Experimental design and response surface modeling provide an accurate and much cheaper framework for calculating effective properties. Effective properties are calculated at a few chosen points (the design) by simulating flow with a fine grid. Best-fit polynomials can be computed using response surface methods. Models based on outcrop exposures of the Frewens Sandstone, a fluvial-deltaic deposit in Central Wyoming are upscaled using response surfaces with few fine scale simulations. Uncertainty in effective properties and their sensitivity to factors in the reservoir description can be accurately and inexpensively investigated using response surfaces. Probability distributions of the effective properties are derived by conducting Monte Carlo simulations with the response surfaces
Development of a framework for parallel reservoir simulation
(2017-09-15) Barrios Molano, Hector Emilio; Sepehrnoori, Kamy, 1951-
Parallel reservoir simulation is a topic of special interest to reservoir engineers and reservoir simulator developers. Parallel reservoir simulators provides several advantages over non-parallel reservoir simulators, such as • Capability to run bigger models. • Capability to have simulation results faster by using several processing units at once. • Not limited to single computer memory. Memory available increases as more computers are used. All these are compelling reasons for reservoir engineers. However, for reservoir simulator developers, the creation of a parallel reservoir simulator is a more complex task than non-parallel simulators. Problems related to parallel implementation such as parallel communication, model division among processors, and the management of data distributed among processors, among others should be addressed and solved on top of the already complex task of simulator development. Hence, development time for parallel reservoir simulators is more time intensive than the traditional development on single processor computers. The objective of this work is to separate the development focus of parallel reservoir simulators in two: parallel development and reservoir simulator development. To achieve such separation, a parallel framework was developed. The framework developed in this work implements and handles the parallel complexity and provides easy to use programming interfaces to accelerate the development of new parallel reservoir simulators or the parallelization of existing ones. The University of Texas Compositional Simulator (UTCOMP) was used with the framework to create a new parallel reservoir simulator. Several cases were used to verify accuracy, to assert usability and to test parallel performance on our new parallel reservoir simulator. The parallel reservoir simulator developed in this work has all of UTCOMP's features and is able to run models with up to 102.4 million cells using up to 1024 processors.
Development of a two-phase flow coupled capacitance resistance model
(2014-12) Cao, Fei, active 21st century; Lake, Larry W.
The Capacitance Resistance Model (CRM) is a reservoir model based on a data-driven approach. It stems from the continuity equation and takes advantage of the usually abundant rate data to achieve a synergy of analytical model and data-driven approach. Minimal information (rates and bottom-hole pressure) is required to inexpensively characterize the reservoir. Important information, such as inter-well connectivity, reservoir compressibility effects, etc., can be easily and readily evaluated. The model also suggests optimal injection schemes in an effort to maximize ultimate oil recovery, and hence can assist real time reservoir analysis to make more informed management decisions. Nevertheless, an important limitation in the current CRM model is that it only treats the reservoir flow as single-phase flow, which does not favor capturing physics when the saturation change is large, such as for an immature water flood. To overcome this limitation, we develop a two-phase flow coupled CRM model that couples the pressure equation (fluid continuity equation) and the saturation equation (oil mass balance). Through this coupling, the model parameters such as the connectivity, the time constant, temporal oil saturation, etc., are estimated using nonlinear multivariate regression to history match historical production data. Incorporating the physics of two-phase displacement brings several advantages and benefits to the CRM model, such as the estimation of total mobility change, more accurate prediction of oil production, broader model application range, and better adaptability to complicated field scenarios. Also, the estimated saturation within the drainage volume of each producer can provide insights with respect to the field remaining oil saturation distribution. Synthetic field case studies are carried out to demonstrate the different capabilities of the coupled CRM model in homogeneous and heterogeneous reservoirs with different geological features. The physical meanings of model parameters are well explained and validated through case studies. The results validate the coupled CRM model and show improved accuracy in model parameters obtained through the history match. The prediction of oil production is also significantly improved compared to the current CRM model. A more reliable oil rate prediction enables further optimization to adjust injection strategies. The coupled CRM model has been shown to be fast and stable. Moreover, sensitivity analyses are conducted to study and understand the impact of the input information (e.g., relative permeability, viscosity) upon the output model parameters (e.g., connectivity, time constants). This analysis also proves that the model parameters from the two-phase coupled model can combine both reservoir compressibility and mobility effects.
Gas storage facility design under uncertainty
(2009-12) Ettehadtavakkol, Amin, 1984-; Jablonowski, Christopher J.; Lake, Larry W.
In the screening and concept selection stages of gas storage projects, many estimates are required to value competing projects and development concepts. These estimates are important because they influence which projects are selected and which concept proceeds into detailed engineering. In most cases, there is uncertainty in all of the estimates. As a result, operators are faced with the complex problem of determining the optimal design. A systematic uncertainty analysis can help operators solve this problem and make better decisions. Ideally, the uncertainty analysis is comprehensive and includes all uncertain variables, and simultaneously accounts for reservoir behavior, facility options, and economic objectives. This thesis proposes and demonstrates a workflow and an integrated optimization model for uncertainty analysis in gas storage. The optimization model is fast-solving and eliminates most constraints on the scope of the uncertainty analysis. Using this or similar workflows and models should facilitate analysis and communication of results within the project team and with other stakeholders.
An integrated geologic model of Valhall oil field for numerical simulation of fluid flow and seismic response
(2007-05) Chakraborty, Samarjit; Ferguson, Robert J., Ph. D.
Time-lapse seismic monitoring promises to be a valuable tool for reservoir engineering as it provides dynamic data over the entire field rather than the spatially limited production data. In this thesis, I develop a link between computerized reservoir simulation, rock physics, and seismic analysis. I present an example study of time-lapse seismic effects in a sequence of reservoir simulation, rock physics, and seismic forward modeling. The thesis includes a case-study of the Valhall field which I propose be used for an integrated geologic model for fluid flow and seismic simulation. I combine fluid flow simulation studies with a parallel flow simulation code IPARS to obtain computed pore pressure and oil saturation at different spatial location as a function of time. The reservoir model for fluid flow simulation input is linear and isotropic. The reservoir model has an injection well below the oil-water contact and a producer well at a shallower level. The variations of pore pressure due to injection and production cause 3-D multi-phase fluid flow in the reservoir with time. I develop a rock physics mapping code to estimate the P-wave and S-wave seismic velocities and densities for seismic forward modeling from pore pressure and water and oil saturation obtained by fluid flow simulation. The rock physics code uses Gassmann's relations for fluid substitution to compute the seismic rejection parameters. Migrated depth sections show brightening of amplitude values near the producer well as a function of time. Rejections from the production zone appear stronger indicating high oil saturation values with increasing production. I develop a case-study of the Valhall Field to make an integrated geologic model for fluid flow and seismic simulation. Based on an initial description of reservoir geology, I combine rock-physics measurements, fluid properties, geomechanics,seismic, well, and checkshot data, to build an integrated model for simulations of subsurface fluid-flow and surface seismic data.
Investigation of analytical models incorporating geomechanical effects on production performance of hydraulically and naturally fractured unconventional reservoirs
(2014-08) Aybar, Umut; Sepehrnoori, Kamy, 1951-; Patzek, Tadeusz W.
Petroleum and Geosystems Engineering
Quantification of production recovery using probabilistic approach and semi-analytical model for unconventional oil reservoirs
(2015-12) Choi, Bong Joon; Srinivasan, Sanjay; Sepehrnoori, Kamy, 1951-
Decline curve analysis is widely applied for production forecasting in oil & gas industry. However, many models do not work for super-tight, unconventional wells with dominant fracture flows. Some novel decline models have been introduced for unconventional plays, but the transition time between the transient and pseudo-steady flow period is difficult to model with such pure empirical relations. Consequently, the decline projections are often inaccurate and furthermore, they are difficult to quantify the uncertainty associated with the predictions. To address these issues, a combined probabilistic approach is proposed that uses a dual-porosity semi-analytical decline model within an extended bootstrap framework in order to provide estimates for the P10, P50 and P90 production profiles. The probabilistic method employed in this research is a data-generative approach that employs modified bootstrap method to generate multiple decline model projections. The semi-analytical model is an approximate decline model that optimizes parameters describing flow in matrix-fracture systems using the observed production profile. In the proposed method, probabilistic approach and semi-analytical decline model are combined. The modified approach is compared to the performances developed with Arps’ hyperbolic model. Both models are fitted by optimizing respective parameters and 50 synthetic data sets are used to draw confidence interval projections. The probabilistic approach is extended by proposing alternate blocking techniques – variance of the mean and analysis of the variance (ANOVA), in place of a scheme based on the autocorrelation exhibited by the decline data, originally implemented by other researchers. The cumulative production and forecast period production errors are calculated for these alternative schemes. For all proposed applications, two unconventional, horizontal oil wells are used to test the results. Both these wells exhibit sharp decline in production rate in the first few months that is related to fracture flow regimes. The results show that the proposed application of semi-analytical model with probabilistic approach significantly improved the projections. The implementation of alternate blocking techniques also show improvement in confidence interval projections, The resultant uncertainty distributions are more accurate and precise than those obtained using the autocorrelation based schemes. The combined results show that ANOVA blocking technique outperformed the other two techniques.
A sensitivity study on modified salinity waterflooding and its hybrid processes
(2016-05) Bissakayev, Beibit; Sepehrnoori, Kamy, 1951-; Kazemi Nia Korrani, Aboulghasem
Waterflood is one of the most widely used techniques in enhanced oil recovery. In 1990s researchers came to conclusion that the chemistry of the injected water can be important in improving oil recovery. The low salinity water injection (LoSal® ) has become one of the promising topics in the oil industry. It is believed that the main mechanism for incremental oil recovery in low salinity flooding is wettability alteration. Several papers discussed that the wettability alteration from oil-wet to mixed- or water-wet takes place due to clay swelling and expanding of double layer in sandstones and calcite dissolution along with rock surface reactions in carbonates. However, there is no consensus on a single main mechanism for the low salinity effect on oil recovery. The main objective of this research is to conduct sensitivity analysis on main parameters in low salinity waterflooding and its hybrid processes affecting oil recovery in carbonates. We compare results by using coupled reservoir simulator UTCOMP-IPhreeqc. UTCOMP is the compositional reservoir simulator developed at the Center for Petroleum and Geosystems Engineering in The University of Texas at Austin. IPhreeqc is the module-based version of the PHREEQC geochemical package, a state-of-the-art geochemical package developed by the United States Geological Survey (USGS). We investigate the effect of low salinity water and carbon dioxide on oil recovery from carbonates by modeling the processes through the UTCOMP-IPhreeqc simulator. We perform sensitivity analysis on continuous gas injection (CGI), water-alternating-gas (WAG) flooding, and polymer-water-alternate-water (PWAG) flooding. We study the significance of reservoir parameters, such as reservoir heterogeneity (Dykstra-Parsons coefficient, Vdp, and crossflow, kv/kh), the salinity of injected water, the composition of gas, and polymer concentration in polymer-water solution on cumulative oil recovery. Moreover, we study the importance of inclusion of the hydrocarbon CO2 impact on the aqueous-rock geochemistry by comparing two scenarios where in one scenario the hydrocarbon CO2 effect is included in UTCOMP-IPhreeqc whereas in the other one the effect is neglected. Finally, we perform sensitivity analysis on PWAG flooding for most influential design parameters using Design of Expert software. The reservoir parameters, such as average reservoir permeability, reservoir heterogeneity, and crossflow and injected polymer-water solution parameters, such as polymer concentration and salinity of injected water are optimization parameters in this study.
Simple mechanistic modeling of recovery from unconventional oil reservoirs
(2015-05) Ogunyomi, Babafemi Anthony; Lake, Larry W.; Sepehrnoori, Kamy; Srinivasan, Sanjay; Jablonowski, Christopher J.; Bickel, James E.
Decline curve analysis is the most widely used method of performance forecasting in the petroleum industry. However, when these techniques are applied to production data from unconventional reservoirs they yield model parameters that result in infinite (nonphysical) values of reserves. Because these methods were empirically derived the model parameters are not functions of reservoir/well properties. Therefore detailed numerical flow simulation is usually required to obtain accurate rate and expected ultimate recovery (EUR) forecast. But this approach is time consuming and the inputs in to the simulator are highly uncertain. This renders it impractical for use in integrated asset models or field development optimization studies. The main objective of this study is to develop new and “simple” models to mitigate some of these limitations. To achieve this object field production data from an unconventional oil reservoir was carefully analyzed to identify flow regimes and understand the overall decline behavior. Using the result from this analysis we use design of experiment (DoE), numerical reservoir simulation and multivariate regression analysis to develop a workflow to correlate empirical model parameters and reservoir/well properties. Another result from this analysis showed that there are at least two time scales in the production data (existing empirical and analytical model do not account for this fact). Double porosity models that account for the multiple time scales only have complete solutions in Laplace space and this make them difficult to use in optimization studies. A new approximate analytical solution to the double porosity model was developed and validated with synthetic data. It was shown that the model parameters are functions of reservoir/well properties. In addition, a new analytical model was developed based on the parallel flow conceptual model. A new method is also presented to predict the performance of fractured wells with complex fracture geometries that combines a fundamental solution to the diffusivity equation and line/surface/volume integral to develop solutions for complex fracture geometries. We also present new early and late time solutions to the double porosity model that provide explicit functions for skin and well/fracture storage, which can be used to improve the characterization of fractured horizontal wells from early-time production data.
Surface-coated silica nanoparticles for conformance control of buoyancy-driven CO₂ flow
(2017-08-11) Senthilnathan, Siddharth; DiCarlo, David Anthony, 1969-; Daigle, Hugh
In light of growing concerns over rising atmospheric concentrations of greenhouse gases like carbon dioxide (CO₂), carbon capture and storage (CCS) has been suggested as a means to reduce the rate of net addition of CO₂ to the atmosphere. One potential CCS method involves injecting CO₂ into deep saline aquifers, where they are designed to reside for long periods of time. High-pressure and high-temperature CO₂/brine flow through porous media is the subject of active research, but faithfully recreating the conditions and forces found deep in the subsurface remains a challenge. In particular, the role of buoyant forces in transporting CO₂ must be studied further, since the long-term migration of CO₂ is dominated by buoyancy. This study consists of two parts. Chapter 1 discusses buoyancy as relevant to the context of CO₂ sequestration and prior methods used to study buoyancy-dominated flow. Four methods to experimentally recreate buoyancy-driven flow in high-pressure corefloods are presented: “inject low and let rise,” progressive pressure increase, simplified Darcy’s Law, and the Buckley-Leverett approach. Chapter 2 investigates the potential of using surface-coated silica nanoparticles to improve the conformance of CO₂ during flow through aquifers. The Buckley-Leverett approach is used to determine a single buoyancy-driven flow rate, and a vertical coreflood is conducted using this flow rate. Core-average saturation and pressure drop measurements across the core are measured, and the in-situ CO₂ distribution is visualized by taking axial X-ray CT scans of the core during the experiment. The effect of the nanoparticles is studied by conducting the experiment with three different nanoparticle concentrations: 0 wt% (as a control), 0.5 wt%, and 5 wt%. The addition of 0.5 wt% of nanoparticles (NP) does not markedly improve the conformance of CO₂ when compared to the control. However, at concentrations of 5 wt% NP, steady-state and residual CO₂ saturation increases, sweep efficiency increases, and CO₂ mobility decreases significantly when compared to the control. The lack of effectiveness of the 0.5 wt% formulation may be due to the influence of perpendicular-to-flow bedding layers that are present in the cross-bedded sandstone core used in the experiments. There are mixed indications regarding the suitability of the Buckley-Leverett approach to predicting the buoyancy-driven flow regime.
Understanding unstable immiscible displacement in porous media
(2015-05) Doorwar, Shashvat; Mohanty, Kishore Kumar; Pope, Gary; DiCarlo, David; Huh, Chun; Weerasooriya, Upali; Hidrovo, Carlos
Our global heavy and viscous oil reserves are immense. 70% of our current global oils reserves are viscous or heavy. For an energy secure future, exploitation of heavy oil reserves is necessary to mitigate the impact of steadily declining conventional reserves. Though most viscous and heavy oils are produced by thermal stimulation, several cases do exist where thermal methods are neither technically feasible nor economically profitable. In such cases, non-thermal EOR methods have to be applied. Any displacement process at such high viscosity ratio will be influenced by viscous fingering. Polymers are typically added to the water to stabilize the displacement but for oils above a couple of 100 cp viscosity a stable displacement is not feasible. As unstable displacements are not very well understood, visualization along with experimentation is critical for understanding and modeling the process. In this study, multi-scale experimental strategy was employed; experiments were conducted in cores at lab-scale to generate quantifiable data and were repeated in small micro-fluidic cells for visualization of the mechanism. Polymer flood as an alternative non-thermal process in a structurally complex carbonate formation was tested. In carbonates formations, thermal methods are not preferred as mineral dissolution and precipitation lead to formation damage. Effect of timing of polymer flood was studied in great details. Result from both the micromodels and core-floods indicate that for heavy oils, unlike light oils, timing of polymer injection is not critical and a tertiary polymer flood at the completion of waterflood can also produce significant incremental oil. In some cases, tertiary polymer flood even out-performs a secondary polymer flood. A major problem with modeling and predicting the performance of an unstable flood is largely due to our inability to accurately capture viscous fingering or its effects. Viscous fingering is a complex phenomenon and is dependent on several parameters such as injection rate, viscosity ratios, heterogeneity and dimensions. The micromodels were used to visualize the variation in flow pattern at different viscosity ratio and injection rates while core floods provided essential modeling data. Based on the results two new models were developed: a simplified network model that could accurately predict the viscous fingers for all viscosity ratios and a lumped model that capture the effect of viscous fingers at larger scales through pseudo-relative permeability functions. A dimensionless scaling parameter similar to the instability parameter of Peters and Flock (1981) was also developed that is useful in predicting the recoveries of all unstable displacement at various viscosity ratios, injection rate, permeability and width. The scaling parameter showed excellent fit with experimental data of over 60 experiments.
Wettability alteration for carbonate and sandstone formations
(2024-05) Reinoso, Bruno ; Mohanty, Kishore Kumar
In tight carbonate reservoirs, waterflood recovery rates are typically low due to their inherent heterogeneity and oil-wet or mixed-wet characteristics. Wettability alteration is a promising approach for enhancing oil recovery in such reservoirs. Conversely, sandstone reservoirs often exhibit water-wet characteristics attributed to the presence of negatively charged mineral components like quartz and clays. In these formations, low salinity water does not have the potential to induce wettability alteration. This study aims to improve oil recovery in such a carbonate reservoir in West Texas. The mineralogy is determined by XRD analysis. The zeta potential is measured for the drill cuttings and reservoir core. Contact angles are measured on core trims, and imbibition experiments are conducted to evaluate wettability alteration. The optimum salinity was determined to be 40 times diluted produced water from zeta potential measurements. The synergy between low-salinity water and surfactants yielded more than 40% oil recovery in spontaneous imbibition experiments. The addition of sulfate ions and weak acids improved spontaneous imbibition. The results of core flood tests underscored the efficacy of surfactants in enhancing oil recovery through wettability alteration after waterflooding. This study highlights the potential of low-salinity and surfactant-assisted flooding to enhance oil recovery in limestone reservoirs. In addition, this study investigates the impact of low salinity water on enhancing oil recovery in a sandstone reservoir located in the Oriente Basin of Ecuador. Elemental and mineral characterization was conducted through X-ray diffraction (XRD) and energy-dispersive X-ray spectroscopy (EDX) analyses. Water compatibility tests were performed to ensure compatibility among all brines used in the study. Zeta potential analysis was employed to identify the optimal salinity range for enhanced oil recovery. The Hollin brine (2353 ppm) closely approximated this range and was selected for further experiments. Contact angle measurements provided valuable insights into the effect of low salinity on wettability alteration in the sandstone samples. Coreflood experiments were conducted to determine the potential of low-salinity water following traditional waterflooding. In the coreflood experiment carried out in the T reservoir, we obtained a 10% increase in oil recovery when using low-salinity water. Similarly, in the U reservoir, the use of low salinity water resulted in a 2% oil increment, primarily due to the presence of a small amount of clays and the specific wettability characteristics of the rock samples.