The utilization of synergistic mixtures of nanoparticles (NPs) and surfactants for enhanced oil recovery (EOR) has drawn increasing scientific attention. In this study, a series of coarse-grained (CG) molecular dynamics (MD) models were built to study the behaviors of NPs and surfactants in the vicinity of the oil/water interface. Hydrophilic, hydrophobic, and amphiphilic NPs were constructed to investigate the effect of hydrophobicity on the ability of NPs in term of interfacial tension (IFT) reduction. The synergistic effect of surfactants and NPs were also studied.
Surfactants and amphiphilic NPs can both accumulate at the interface of oil and water, while hydrophilic and hydrophobic NPs stay in water or oil phase. The NPs with various ratios of hydrophobic to hydrophilic domains were investigated to determine the types of NPs that result in the most IFT reduction. The comparison of IFTs indicates that amphiphilic NPs has a better ability to assist surfactants in further reducing the interfacial tension. Meanwhile, surface modification and the presence of surfactants can prevent the aggregation of NPs.
These MD simulation results allow us to figure out the physical behavior of NPs and surfactants at the oil/water interfaces. Analysis of the results can further assist the NPs synthesis for surfactant and/or surfactant-nanoparticle EOR applications in unconventional reservoirs.
Enhanced Oil Recovery (EOR) is well known for its potential to produce residual oil after the primary and secondary oil recovery. The residual oil is trapped in the narrow throat due to high capillary pressure, which is influenced by rock wettability and oil/water interfacial tension (IFT) (Wu et al., 2008). Surfactants have been widely investigated and employed in the EOR process to reduce the IFT and to alter the wettability (Sheng et al. 2015; Kamal et al., 2017; Negin et al., 2017). However, during the surfactant flooding, surfactants can adsorb onto the rock surfaces. This may result in the reduction of their concentrations, which significantly reduce the efficiency of surfactants in practical applications. The high cost of surfactants also makes this potential loss a critical issue. Many researchers have focused their studies on reducing the adsorption of surfactants by adding various materials in the chemical formulations.
In this study, conceptual numerical simulation models, with geomechanical properties incorporated, were employed to assess whether polymer flooding or a surfactant EOR process could be viable; with minimal damage to permafrost. These simulations considered the geological subdivisions of permafrost distribution in the subsurface which included: an active layer (seasonally frozen ground); taliks (unfrozen ground between the base of the active layer and permafrost layer and within the permafrost layer); and the unfrozen layer below the permafrost zone. In addition, a major oil zone was included in the model underlying the permafrost section. Significant oil recovery values were predicted, both for injection of polymer solutions and surfactant-polymer solutions and with both horizontal and vertical wells. Surprisingly, addition of surfactant provides lower oil recovery than for polymer flooding alone (under same injection slug size, when all subdivisions were considered in the model). This result appeared to occur because the thermodynamics build into models allows the surfactant formulation to freeze easier than the polymer solution without surfactant. This freezing depletes the surfactant bank, and therefore, lowers oil recovery. On the other hand, this freezing actually promotes growth of the permafrost, whereas, injection of polymer alone causes a mild thawing of the permafrost. One might question whether the thermodynamics built into the simulator are correct, but this result does emphasis that in addition to temperature, the chemistry of the injected formulation may be important in determining the fate of the permafrost. At a certain well distance to permafrost (1,640 ft), horizontal injection wells cause greater thawing of permafrost than vertical wells, when wellbores are close to the taliks. Higher concentration and viscosity of polymer slugs have small potential for thawing permafrost, largely because of the injectivity reduction during polymer flooding (thus allowing slower heat dissipation). Examination of polymer injection as a function of pressure, temperature, and mean stress, suggests that subsidence of permafrost could be negligible. The effects on permafrost subsidence increases modestly as the polymer slug size increases, and decreases modestly as the surfactant-polymer slug size increases. As huge heavy oil reserves exist in Canada and Alaska's North Slope regions, continued resource development in these regions is likely. Therefore, a thorough understanding is required in considering the long-term impact on permafrost stability with the use of modern EOR processes implemented in this unique environment.
Martini, Brigette (Corescan Inc.) | Bellian, Jerome (Whiting Petroleum Corporation) | Katz, David (Encana Corporation) | Fonteneau, Lionel (Corescan Pty Ltd) | Carey, Ronell (Corescan Pty Ltd) | Guisinger, Mary (Whiting Petroleum Corporation) | Nordeng, Stephan H. (University of North Dakota)
Hyperspectral core imaging studies of the Bakken-Three Forks formations over the past four years has revealed non-destructive, high resolution, spatially relevant insight into mineralogy, both primary and diagenetically altered that can be applied to reservoir characterization. While ‘big’ data like co-acquired hyperspectral imagery, digital photography and laser profiles can be challenging to analyze, synthesize, scale, visualize and store, their value in providing mineralogical information, structural variables and visual context at scales that lie between (and ultimately link) nano and reservoir-scale measurements of the Bakken-Three Forks system, is unique.
Simultaneous, co-acquired hyperspectral core imaging data (at 500 μm spatial resolution), digital color photography (at 50 μm spatial resolution) and laser profiles (at 20 μm spatial and 7 μm vertical resolution), were acquired over 24 wells for a total of 2,870 ft. of core, seven wells of which targeted the Bakken-Three Forks formations. These Bakken-Three Forks data (~5.5 TB) represent roughly 175,000,000 pixels of spatially referenced mineralogical data. Measurements were performed at a mobile Corescan HCI-3 laboratory based in Denver, CO, while spectral and spatial analysis of the data was completed using proprietary in-house spectral software, offsite in Perth, WA, Australia. Synthesis of the spectral-based mineral maps and laser-based structural data, with ancillary data (including Qemscan, XRD and various downhole geophysical surveys) were completed in several software and modelling platforms.
The resulting spatial context of this hyperspectral imaging-based mineralogy and assemblages are particularly compelling, both in small scale micro-distribution as well as borehole scale mineralogical distributions related to both primary lithology and secondary alteration. These studies also present some of the first successful measurement and derivation of lithology from hyperspectral data. Relationships between hyperspectral-derived mineralogy and oil concentrations are presented as are separately derived structural variables. The relationship between hyperspectral-based mineralogy to micro-scale reservoir characteristics (including those derived from Qemscan) were studied, as were relationships to larger-scale downhole geophysical data (resulting in compelling correlations between variables of resistivity and hyperspectral-mineralogy). Finally, basic Net-to-Gross calculations were completed using the hyperspectral imaging data, thereby extending the use of such data from geological characterizations through to resource estimations.
The high-fidelity mineralogical maps afforded by hyperspectral core imaging have not only provided new geological insight into the Bakken-Three Forks formations, but ultimately provide improved well completion designs in those formations, as well as a framework for applying the technology to other important unconventional reservoir formations in exploration and development. The semi-automated nature of the technology also ushers in the ability to consistently and accurately log mineralogy from multiple wells and fields globally, allowing for advanced comparative analysis.
Geri, Mohammed Ba (Missouri University of Science and Technology) | Ellafi, Abdulaziz (University of North Dakota) | Ofori, Bruce (Missouri University of Science and Technology) | Flori, Ralph (Missouri University of Science and Technology) | Sherif, Huosameddin (Missouri University of Science and Technology)
Recent studies have presented successful case studies of using HVFR fluids in the field. Reported cost reductions from using fewer chemicals and less equipment on the relatively small Marcellus pads when replacing linear gel fluid systems by HVFR. The investigation provided a screening guideline of utilizing HVFRs in terms of its viscosity and concentration. The study notes that in field application the average concentration of HVFRs is 2.75 gpt (gal per 1,000 gal)
Three different scenarios were selected to study fluid type effect using 3D pseudo simulator; as a first scenario; fracture dimensions as a second scenario; the last scenario was proppant type. The first scenario consists of two cases: utilizing HVFR-B as new fracture fluid in 20% of produced water was investigated in scenario I (base case). Comparison between HVFR and linear gel in the Middle Bakken was investigated in Case II of the first scenario. At the second scenario, fracture half-length was studied. Proppant distribution impact by using HVFR in Bakken formation was analyzed as the third scenario. The final scenario investigated the pumping flow rate influence on proppant transport of using HVFR. The concentration of HVFR-B was 3 gpt and the proppant size was 30/50 mesh. The treatment schedule of this project consists of six stages. The proppant concentration was increased gradually from 0.5 ppt to 6 ppt at the later stage.
In the case of using HVFR-B the fracture half-length was approximately 1300 ft while using linear gel created smaller fracture half-length. In contrast, using linear gel makes the fracture growth increase rapidly up to 290 ft as showed. To conclude, using HVFR-B created high fracture length with less fracture height than linear gel. Additionally, in using HVFR-B, the average fracture height was approximately 205 ft while using linear gel created increasing of the fracture growth rapidly up to 360 ft which represent around 43% increasing of the fracture height. In studying the impact of fracture half-length on proppant transport, increasing fracture half-length from 250 ft to 750 ft leads to the fracture growth rapidly up to 205 ft
Studying the impact of proppant size effect on proppant transport, we observed changing fracture conductivity across fracture half-length. Thus, the fracture height increasing with decreasing proppant mesh size. Fracture height increased from 193 ft to 206 ft by changing proppant mesh size from 20/40 to 40/70 mesh. With flow rate impact on proppant transport, it was observed that, the fracture height increases by increasing the pump rate. Utilizing HVFR-B in the fracture treatment provides higher absolute open flow rate (AOF) which is around 2000 BPD. On the other hand, the outcomes of using linear gel has less AOF that about 1600 BPD. Also, Increasing the Xf and proppant mesh size leads to increase the AOF.
This project describes comparison of the successful implementation of utilizing HVFR as an alternative fracturing system to linear gel.
Temizel, Cenk (Aera Energy) | Balaji, Karthik (University of North Dakota) | Canbaz, Celal Hakan (Ege University) | Palabiyik, Yildiray (Istanbul Technical University) | Moreno, Raul (Smart Recovery) | Rabiei, Minou (University of North Dakota) | Zhou, Zifu (University of North Dakota) | Ranjith, Rahul (Far Technologies)
Due to complex characteristics of shale reservoirs, data-driven techniques offer fast and practical solutions in optimization and better management of shale assets. Developments in data-driven techniques enable robust analysis of not only the primary depletion mechanisms, but also the enhanced oil recovery in unconventionals such as natural gas injection. This study provides a comprehensive background on application of data-driven methods in oil and gas industry, the process, methodology and learnings along with examples of data-driven analysis of natural gas injection in shale oil reservoirs through the use of publicly-available data.
Data is obtained and organized. Patterns in production data are analyzed using data-driven methods to understand key parameters in the recovery process as well as the optimum operational strategies to improve recovery. The complete process is illustrated step-by-step for clarity and to serve as a practical guide for readers. This study also provides information on what other alternative physics-based evaluation methods will be able to offer in the current conditions of data availability and the understanding of physics of recovery in shale oil assets together with the comparison of outcomes of those methods with respect to the data-driven methods. Thereby, a thorough comparison of physics-based and data-driven methods, their advantages, drawbacks and challenges are provided.
It has been observed that data organization and filtering takes significant time before application of the actual data-driven method, yet data-driven methods serve as a practical solution in fields that are mature enough to bear data for analysis as long as the methodology is carefully applied. The advantages, challenges and associated risks of using data-driven methods are also included. The results of comparison between physics-based methods and data-driven methods illustrate the advantages and disadvantages of each method while providing the differences in evaluation and outcome along with a guideline for when to use what kind of strategy and evaluation in an asset.
A comprehensive understanding of the interactions between key components of the formation and the way various elements of an EOR process impact these interactions, is of paramount importance. Among the few existing studies on natural gas injection in shale oil with the use of data-driven methods in oil and gas industry include a comparative approach including the physics-based methods but lack the interrelationship between physics-based and data-driven methods as a complementary and a competitor within the era of rise of unconventionals. This study closes the gap and serves as an up-to-date reference for industry professionals.
Gaither Draw Unit is a heterogeneous and tight formation with an average permeability less than 0.1 mD. After more than 1.7 MMSTB water injection, there was no clear indication or benefit of the injected water from any producer. However, knowing the distribution of the injected water is critical for future well planning and quantifying the efficiency of injection. The objective of this study is to show how the Capacitance-Resistance Model (CRM) was used on this field and validated using other independent methods.
The CRM model describes the connectivity and the degree of fluid storage quantitatively between injectors and producers from production and injection rates. Rooted in material balance, signals from injectors to producers can be captured in the CRM. Using constrained nonlinear multivariable optimization techniques, the connectivity is estimated in the selected portion of the field through signal analysis on injection and production rates. In this tight formation, the whole field is divided into seven regions with one injection well and surrounding producers to conduct CRM analysis. We further use integrated but independent approaches to validate the results from CRM. The validation includes full field modeling and history match and fluid level measurement using echometering technology.
This paper focuses on a real field water flooding project in Gaither Draw Units(GDU). CRM is used to detect reservoir heterogeneity through quantifying communication between injectors and producers, and attains a production match. The fitting results of connectivity through CRM indicate permeability regional heterogeneity, which is consistent with full field modelling. The history matched full field model presents the saturation distribution showing that the majority of injected water mainly saturates the surrounding regions of injectors, and the low transmissibility slows down the pressure dissipation. Overall, the comprehensive interpretation obtained through these three independent methods is consistent, and is very useful in planning infill well drilling and future development plan for the Gaither Draw Units.
This paper shows that it is critical to integrate different sources of data in reservoir management through a field case study. The experience and observations from this asset can be applied to other tight formations being developed with water flooding projects.
In recent years, the exploration and production of oil and gas from Bakken formation in Williston Basin have proceeded quickly due to the application of multi-stage fracturing technology in horizontal wells. Knowledge of the rock elastic moduli is important for the horizontal drilling and hydraulic fracturing. Although static moduli obtained by tri-axial compression test are accurate, the procedures are cost expensive and time consuming. Therefore, developing correlation to predict static moduli from dynamic moduli, which is calculated from sonic wave velocities, is meaningful in cutting cost and it makes the unconventional oil and gas exploration and production more efficient.
Literature review indicates such a correlation is not available for Bakken formation. This may be attributed to the extremely low success rate in Bakken core sample preparation and not enough published data to develop correlation to relate dynamic moduli to static moduli. This study measures and compares the moduli obtained from sonic wave velocity tests with deformation tests (tri-axial compression tests) for the samples taken from Bakken formation of Williston Basin, North Dakota, USA. The results show that the dynamic moduli of Bakken samples are considerably different from the static moduli measured by tri-axial compression tests. Correlations are developed based on the static and dynamic moduli of 117 Bakken core samples. The cores used in this study were taken from the core areas of Bakken formation in Williston Basin. Therefore, they are representatives of the Bakken reservoir rock. These correlations can be used to evaluate the uncertainty of Bakken formation elastic moduli estimated from the seismic and/or well log data and adjust to static moduli at a lower cost comparing with conducting static tests. The correlations are crucial to understand the rock geomechanical properties and forecast reservoir performance when no core sample is available for direct measurement of static moduli.
Flow pattern of a multi-phase flow refers to the spatial distribution of the phase along transport conduit when liquid and gas flow simultaneously. The determination of flow patterns is a fundamental problem in two-phase flow analysis, and an accurate model for gas-liquid flow pattern prediction is critical for any multiphase flow characterization as the model is used in many applications in petroleum engineering. The objective of this study is to present a new model based on machine learning techniques and more than 8000 laboratory multi-phase flow tests.
The flow pattern is affected by fluid properties, in-situ flow rates of liquid and gas, and flow conduit geometry and mechanical properties. Laboratory data since 1950s have been collected and more than 8000 data points had been obtained. However, the actual flow conditions are significantly different with any laboratory settings. Therefore, several dimensionless variables are derived to characterize these data points first. Then machine learning techniques were applied on these dimensionless variables to develop the flow pattern prediction models. Applying hydraulic fundamentals and dimensional analysis, we developed dimensionless numbers to reduce number of freedom dimensions. These dimensionless variables are easy to use for upscaling and have physical meanings. We converted the collected data from actual laboratory measurement to the variations of these dimensionless variables. Machine learning techniques on the dimensionless variable significantly improved their predictive accuracy. Currently the best matching on these laboratory data was about 80% using the most recently developed semi-analytical models. Using machine learning techniques, we improved the matching quality to more than 90% on the experimental data.
This paper applies machine learning techniques on flow pattern prediction, which has tremendous practical usages and scientific merits. The developed model is better than current existing semi-analytical or classical correlations in matching the laboratory database.
The supersonic separation is a new approach to dehydrate the natural gas in recent years. In the conventional structure, the straight tube is typically combined with a cyclone to create a strong vortex flow. The shock wave usually occurs near the swirling device in the supersonic separator, which can make the flow unstable and decrease the separation efficiency. Due to removing the negative effects of the shockwave, a newtype helical guide blade is designed as the swirling device, installed in the separate straight tube in the supersonic cyclone separator. The flow characteristics in the supersonic separator was investigated and the geometry structure was optimized by performing the computational fluid dynamics modeling methods. The optimization results showed that the model with a converging tube of 190 mm length, a diverging tube of half-cone angle of 5 and a single blade installed in the middle position, is the best supersonic separator model in the dehydration process, which can create the most stable flow field and achieve the optimum separation. In addition, when the outlet back pressure in the diffuser tube is 1 Mpa 1.5 Mpa, the separation performance will be better.
Cores can be considered the ground truth only if we eliminate or minimize their damage during core cutting, tripping, and surface handling. Such damage would adversely alter their properties. An important source of core damage is during tripping, when quick decompression might cause damage because of the induced microfractures. In this paper, a state-of-the-art geomechanical model is introduced and applied for determining the safe-tripping rates.
The thermo-poroelastic (T-P-E) geomechanical approach used in this study includes the mathematical derivation of the diffusion time required for the imposed pore-pressure difference to dissipate while also considering the effects caused by the temperature changes, mudcake, and swabbing. The work uses different approaches for fluid modeling in a transient manner during tripping for the water-bearing, gas-bearing, and oil-bearing cores.
In this work, the hydraulic diffusivity and the fluid type have been introduced as the main factors controlling the maximum allowable safe-tripping rates. A relationship between the allowable decompression rate and the hydraulic diffusivity will be presented for each specified fluid type. In addition, the results indicate that water-bearing cores can be safely tripped as quickly as the normal tripping speed of the wireline, even with a core that has a permeability as low as 0.01 md. For gas- and oil-bearing cores, the safe-tripping rates are determined to be much less than the water-bearing cores because the fluids expand with the pressure drop along the journey to the surface. The results show that the tripping rate is the lowest for the oil-bearing cores, particularly in the vicinity of the bubblepoint and gas critical pressure (because the gas expansion pushes the oil and applies significant viscous forces across the core pore throats).
This paper is a novel work developing T-P-E and mathematical models for the case of core tripping considering the effects of pore-pressure change, temperature change, mudcake, and swabbing. The hydraulic diffusivity and the fluid type have been considered as the controlling factors. The approach has been applied for modeling the tripping of water-, gas-, and oil-bearing cores to provide maximum allowable tripping rates.