Kuznetsov, Oleksandr (Baker Hughes) | Mazyar, Oleg (Baker Hughes) | Agrawal, Devesh (Baker Hughes) | Suresh, Radhika (Baker Hughes) | Feng, Xianhua (Baker Hughes) | Behles, Jackie (Baker Hughes) | Khabashesku, Valery (Baker Hughes)
Oil sand ore flotation is a primary method of bitumen recovery from mined Athabasca tar sands. In bitumen flotation, suspended biwettable ore fines, such as clays, tend to migrate to oil-water interfaces, creating slime coating on liberated bitumen droplets. Slime coating significantly reduces the efficiency of the flotation process and overall oil recovery. Ultra-dispersed hydrophilic silica nanoparticles were found to stabilize biwettable ore fines in an aqueous phase by adsorbing onto fines surfaces, even at concentrations as low as 50 ppm. As a result, fine solids move away from oil/water interfaces, reducing the slime coating and increasing bitumen recovery during flotation of low-grade ore by more than 5%. The addition of nanoparticles has no negative effect on froth quality or oil, water and solid separation in naphthenic and paraffinic froth treatment processes. Detailed molecular dynamics (MD) simulations revealed mechanisms that improve bitumen liberation from mined oil sands in a flotation process. The studies demonstrated that colloidal nanoparticles affect many stages of the bitumen extraction process from bitumen separation to clay wettability alteration.
Given limited CO2 supply, operational constraints, and pattern specific reservoir performance, WAG schedule can be customized such that NPV or other metrics are optimized. Depending on the WAG schedule, recovery can fluctuate between 5–15% at the pattern scale due to reservoir heterogeneity causing variations in sweep efficiency. An analytical method was developed to optimize WAG schedules that couples traditional reservoir modeling and simulation with machine learning, enabling the discovery of optimal WAG schedules that increase recovery at the pattern level. A history-matched reservoir model of Chaparral Energy's Farnsworth Field, Ochiltree County, TX was sampled intelligently to perform predictive reservoir flow simulations and artificially build an intelligent reservoir model that samples a broad range of possible WAG scenarios for optimization. The intelligent model generates the next "best" sample to investigate in the numerical simulator and converges on the optima, quickly reducing the number of runs investigated. Results in this paper demonstrate that there can be significant improvements in net present value as well as net utilization rates of CO2 using this analytical technique. The WAG design generated by the intelligent reservoir model should be deployed in the field in early 2016 for validation. It is intended that the intelligent reservoir model will be updated on a regular basis as injection and production data is obtained. This effort represents the beginning of a paradigm shift in the application of modeling and simulation tools for significant improvements in field production operations.
Post-fracturing production data analysis indicates stimulation of some west Texas wells with surfactant additives did not enhance production as high as expected. Analysis of flowback and produced water for surfactant residues revealed 99% of surfactant was retained inside wells (
Literature precedent exists that polyelectrolyte (PET)-based SAs could significantly reduce surfactant adsorption not only onto a variety of outcrop minerals (Carlpool dolomite, calcite, kaolinite, Berea sandstone, Indiana limestone, etc.) and metal oxide nanoparticles, but also unconventional shale formulations in which surface area can be up to 700 m2/g. In this study, the adsorptions of surfactant and SA to proppants were first examined. Results indicate no adsorption was observed to proppant for both surfactants and PET-based SAs. SAs (0.5 to 1 gal/1,000 gal (gpt)) were then injected with surfactant (1 to 3 gpt) at an appropriate ratio into column-packed shale formulations (primarily composed of calcite, dolomite, quartz, illite, pyrite, and plagioclase feldspar) to investigate its effectiveness in controlling surfactant retention caused by adsorption. Laboratory testing revealed injection of 3 gpt mixture of surfactant and SA has a similar adsorption profile (surface tension as a function of time) as 3 gpt surfactant alone based on the dynamic surface tension measurement. Notably, the addition of SAs resulted in lower surface tension and enhanced hydrocarbon solubility; and thus, an improved oil recovery by surfactant was achieved as evidenced by the oil recovery tests. Additionally, 68% friction reduction of the fracturing fluid with surfactant and SA was sufficient for the field operation compared to the guar-based fluid used in the hydraulic fracturing applications.
As a result of the laboratory findings, field trials were executed on a three well pad in the Permian basin (PB). For the first 30 days oil and gas production appeared to be significantly higher than the average production from offset wells in the same area that were previously fractured with the same surfactant.
Kim, Ijung (Department of Petroleum and Geosystems Engineering, The University of Texas at Austin) | Worthen, Andrew J. (McKetta Department of Chemical Engineering, The University of Texas at Austin) | Lotfollahi, Mohammad (Department of Petroleum and Geosystems Engineering, The University of Texas at Austin) | Johnston, Keith P. (McKetta Department of Chemical Engineering, The University of Texas at Austin) | DiCarlo, David A. (Department of Petroleum and Geosystems Engineering, The University of Texas at Austin) | Huh, Chun (Department of Petroleum and Geosystems Engineering, The University of Texas at Austin)
The immense nanotechnology advances in other industries provided opportunities to rapidly develop various applications of nanoparticles in the oil and gas industry. In particular, nanoparticle has shown its capability to improve the emulsion stability by generating so-called Pickering emulsion, which is expected to improve EOR processes with better conformance control. Recent studies showed a significant synergy between nanoparticles and very low concentration of surfactant, in generating highly stable emulsions. This study's focus is to exploit the synergy's benefit in employing such emulsions for improved mobility control, especially under high-salinity conditions.
Hydrophilic silica nanoparticles were employed to quantify the synergy of nanoparticle and surfactant in oil-in-brine emulsion formation. The nanoparticle and/or the selected surfactant in aqueous phase and decane were co-injected into a sandpack column to generate oil-in-brine emulsions. Four different surfactants (cationic, nonionic, zwitterionic, and anionic) were examined, and the emulsion stability was analyzed using microscope and rheometer.
Strong and stable emulsions were successfully generated in the combinations of either cationic or nonionic surfactant with nanoparticles, while the nanoparticles and the surfactant by themselves were unable to generate stable emulsions. The synergy was most significant with the cationic surfactant, while the anionic surfactant was least effective, indicating the electrostatic interactions with surfactant and liquid/liquid interface as a decisive factor. With the zwitterionic surfactant, the synergy effect was not as great as the cationic surfactant. The synergy was greater with the nonionic surfactant than the zwitterionic surfactant, implying that the surfactant adsorption at oil-brine interface can be increased by hydrogen bonding between surfactant and nanoparticle when the electrostatic repulsion is no longer effective.
In generating highly stable emulsions for improved control for adverse-mobility waterflooding in harsh-condition reservoirs, we show a procedure to find the optimum choice of surfactant and its concentration to effectively and efficiently generate the nanoparticle-stabilized emulsion exploiting their synergy. The findings in this study propose a way to maximize the beneficial use of nanoparticle-stabilized emulsions for EOR at minimum cost for nanoparticle and surfactant.
Piñerez T., Iván D. (University of Stavanger) | Austad, Tor (University of Stavanger) | Strand, Skule (University of Stavanger) | Puntervold, Tina (University of Stavanger) | Wrobel, Stanislaw (University of Stavanger) | Hamon, Gérald (Total E&P)
Low salinity water injection in sandstone is an emerging technology just on the verge of being implemented full field in the UK and in Alaska, USA. Laboratory studies are important for providing relevant and well interpreted data before performing the field trial. However, laboratory investigations show varying results on low salinity EOR, most probably because of a limited understanding of the nature of the process. Recently we have published a "Smart Water" EOR mechanism where pH changes at the rock surface is inducing the wettability alteration, improving positive capillary forces and microscopic sweep efficiency. Researchers have experienced rather poor low salinity EOR effects from 17 different sandstone outcrops from the USA.
In this work we have investigated 6 of the same 17 outcrops, and according to our chemical understanding, some factors are more important for observing LS EOR effects in sandstone. It is the increase in pH, ?pH, obtained when the high salinity (HS) formation water is displaced by the low salinity (LS) injection water, and it is the initial pH and the amount of active cations (Ca2+) in the formation water that are related to the initial wetting.
We have established a link between the poor low salinity EOR effect from all 6 outcrops and the corresponding pH change observed when switching from high salinity to low salinity injection water. The presence of different types of minerals such as clay, feldspars and anhydrite will influence the pH change, and must be taken into account. Additionally, we have seen that the formation water composition has strong influence on the low salinity EOR effect. Using a formation water with salinity like seawater (FW1 ~35 000 ppm) showed only a minor tertiary low salinity EOR effect, 0.74 %OOIP, corresponding to a low pH gradient of 0.5. While experiments using a high salinity formation water (FW2 ~100 000 ppm) showed a 5 % OOIP recovery, corresponding to a larger pH gradient of 2.0.
The results observed are in agreement with the suggested chemical mechanism for the low salinity EOR effect, confirming that it is the pH gradient that triggers the low salinity EOR effect. In addition, the pH screening test used in this work proved once again to be a reliable tool to evaluate the low salinity EOR potential.
A systematic approach to characterize the mixed wet configurations of various reservoir rocks (sandstone and carbonates) by evaluating their surface energy distributions has been presented in this paper. This approach was tested against the macroscopic spatial distribution of oil-wet and water-wet sites and at different temperatures for validation.
The new approach used to characterize the mixed wettability of a reservoir rock pertains to establishing a relation between the volume fraction of the mixed-wet reservoir rocks and surface energy of the mixture. This approach is based on an accurate description of the various physico-chemical interfacial forces present at the reservoir rock surface using Inverse Gas Chromatography (IGC). Mixed-wet configurations of various reservoir rocks are created by combining water-wet and oil-wet samples of the rock in different volume fractions and shaken together to establish uniform distribution. These samples are then subjected to the IGC analysis at different temperatures to deduce their surface energy distribution. The relation developed herein is tested against spatial heterogeneity by combining the oil-wet and water-wet rock samples in a layered fashion to validate the approach. The complete method to deduce the surface energy distribution of a rock surface using IGC has also been explained in detail.
A definite and conclusive relationship between the surface energy and mixed wettability of silica glass beads, calcite, and dolomite samples was established in this study. The mixed-wet configurations of the rock samples ranged from 0% oil-wet (meaning water-wet samples) to 100% oil-wet samples. The findings indicated that the Lifshitz-van der Waals component of the rock mixture did not undergo any change with change in the wetting state of the system under study. However the acid base components showed a marked decrease with increasing oil wetness before plateauing. Temperature was found to have a profound impact on the surface energy of a rock surface. Spatial heterogeneity by way of layered and segregated distribution of oil-wet and water-wet sites did not affect the eventual surface energy distribution thereby validating the new approach.
Wang, Haitao (Petroleum Exploration & Production Research Institute, Sinopec) | Lun, Zengmin (Petroleum Exploration & Production Research Institute, Sinopec) | Lv, Chengyuan (Petroleum Exploration & Production Research Institute, Sinopec) | Lang, Dongjiang (Petroleum Exploration & Production Research Institute, Sinopec) | Pan, Weiyi (Petroleum Exploration & Production Research Institute, Sinopec) | Luo, Ming (Petroleum Exploration & Production Research Institute, Sinopec) | Wang, Rui (Petroleum Exploration & Production Research Institute, Sinopec) | Chen, Shaohua (Petroleum Exploration & Production Research Institute, Sinopec)
Nuclear magnetic resonance (NMR) was used to investigate the exposure between CO2 and matrix with permeability of 0.218 mD at 40 °C and 12 MPa. Before NMR experiment, the core was saturated with oil. To investigate the effects of exposure time on EOR, the saturated core was exposed to CO2 and T2 test was continuously performed with NMR system until the obtained T2 spectrum was unchanged. After the first exposure, CO2 and matrix reached equilibrium state. The second exposure started when CO2 injection was under a constant pressure of 12 MPa and at a constant rate to keep fresh CO2 in system. The procedure of T2 test was unchanged. The third and fourth exposures were conducted in sequence. The results showed that (1) Oil in all pores can mobilize as exposure time increases. (2) The recovery is 46.6% for oil in pores with the diameter of pore larger than 1 µm, this result is higher than the recovery (12.8%) for oil in pores with the diameter of pore smaller than 1 µm. (3) Recovery can be divided into two stages according to the exposure time: a fast-growing stage and a slow-growing stage. (4) Initially, the oil exists in pores with maximum radius of 21 µm in the originally saturated core. After CO2 injection, oil flows to pores with radius greater than 21 µm, suggesting that oil in tight matrix "diffuses" to the surface of core with exposure between CO2 and matrix. (5) The final recoveries of 1st, 2nd, 3rd, 4th exposure experiments are 23.7%, 7.2%, 2.6% and 1.5%, respectively.
This paper presents a dynamic wettability alteration model based on the Gibbs adsorption isotherm equation. The model is conceptually and thermodynamically developed for ideal surfactant solutions (
The developed models can be tuned with experimental data including the contact angle, relative permeability, and capillary pressure parameters then they can be used to predict the efficiency of surfactant injection processes in naturally fractured reservoirs accordingly.
Improved Oil Reocvery (IOR) technologies may offer a new strategy to improve the initial production (IP) and slow the production decline from oil-rich shale formations. Early implementation of chemical IOR technologies largely have been overlooked during strategic planning of unconventional reservoirs. The purpose of this study is to improve understanding of the dynamic processes of oil displacement by surfactants and to investigate mechanism of how surfactants extract oil. A successful conventional surfactant "huff-n-puff' treatment is described with a focus on any relationship between increased oil production and the surfactant soaking period. Surfactant chemistry has been considered as one of a few ultimate IOR solutions. Despite being well proven as effective chemicals to recover oil from convenetional reservoris, surfactants commonly are used in hydraulic fracturing of unconventional reservoris are just to promote flow back of the injected aqueous fluid over a relatively short time frame. In order to better understand the functionality of surfactants for obtaining favorable oil interaction with both the stimulation fluid and rock matrix, a specifically-designed "oil-on-a-plate" (OOAP) setup and procedure is employed to examine the penetration of surfactant into the oil-film that is adhereing to a solid surface. In addition to the well-recognized spontaneous imbibition and surface wettability alternation processes, surfactant also can gradually penetrate and mobilize oil droplets, resulting in improved oil recovert. If properly selected and designed, the surfactant additives in stimulation/fracturing fluids could have multi-functions towards improving both IP and the longer-term oil production. Besides serving as a demulsifier and flowback enhancer to boost IP, the surfactants could continuously lift-up and mobilize adsorbed oil to increase recoverable oil in place.
Jones, S. A. (Delft University of Technology) | Laskaris, G. (Delft University of Technology) | Vincent-Bonnieu, S. (Delft University of Technology and Shell Global Solutions International) | Farajzadeh, R. (Delft University of Technology and Shell Global Solutions International) | Rossen, W. R. (Delft University of Technology)
Aqueous foams play an important role in many industrial processes, from ore separation by froth flotation to enhanced oil recovery (EOR), where the foam is used as a means of increasing sweep efficiency through oil-bearing rock. The complex, structure-dependent, flow behavior of the foam gives improved penetration of lower-permeability regions. Foam is stabilized by surfactant molecules, and the foam strength is influenced by the surfactant concentration in the water phase. It is therefore of great importance to understand the effect of surfactant concentration on foam processes.
Implicit Texture (IT) foam models eg STARS account for the surfactant effect with functions that depend on surfactant concentration in the water and a few other parameters. However, there is no evidence that these functions are able to capture adequately the effect of surfactant concentration effect. We present a comparative study of foam core-flood experiments with various surfactant concentrations. Core-flood tests were conducted in rock cores with a diameter of 1 cm and length of 17cm, significantly smaller than typical cores. Plots of apparent viscosity vs. injected gas fraction were obtained for surfactant concentrations at the critical micellar concentration (CMC) and above. Bulk foam stability and surface tension were measured for all concentrations, in order to define the CMC and to compare with coreflood results. The experimental results have been matched with the STARS IT foam model and the dependency of model parameters on the surfactant concentration is discussed.
This work found that the IT model is not able to predict the decrease of the foam strength with decreasing surfactant concentration. Instead, the study shows that the effect of surfactant concentration can be correlated with the dry-out function of the IT model, and specifically to the limiting capillary pressure