Determination of residual oil saturation (Sor) is heavily required for evaluating the effect of EOR methods. While there are some methods to determine Sor such as coring, logging, and tracer methods, it is generally accepted that tracer methods are more efficient mainly due to the measurement of large reservoir volume and non-dependency on porosity. Among all proposed tracer methods to determine Sor of EOR methods, only Single Well Chemical Tracer (SWCT) method is widely implemented in the industry.
Several SWCT tests have been carried out in Snorre reservoir to evaluate the effect of injection of high, drill, and lowsal waterflooding. Since characteristics of each SWCT test is unique and often is different even on the same well in various tests, simulation procedure for finding multiple history matches to the measured tracer production from the field is a challenging process. In this paper, the numerical interpretation of first SWCT test after high salinity waterflooding is done. The necessary parameters to model the field test and the value of numerical interpretation of SWCT tests is also introduced. UTCHEM is used as the numerical simulation tool to get an acceptable history match to the measured field data.
The procedure of interpretation is started with a single-layer (ideal) model. The unknown parameters that affect tracer production are grid size, hydrolysis reaction rate, and average Sor are obtained. The Sor is determined 0.24 in the present test in the original reservoir temperature of 194 °F. While ideal model shows a worthy fit, there is still some deviation between measured and modelled profiles at the tail of the curves because of non-ideality effects. Flow irreversibility in layered test zones is considered for departing ideal model from the real test in this sandstone reservoir. The three new unknown parameters of non-ideal model are the number of layers in the test zone, the fraction of total fluid injected and produced from each layer, and the Sor for each layer. In the interpretation of the present test, two other layers are added to determine the effect of flow irreversibility in test zone. The main layer, the early layer, and the late layer accepted and produced 52%, 17%, and 31% of the total injected tracer, respectively. The average Sor of 0.22, 0.24, and 0.26 is resulted to the main layer, the early layer, and the late layer, respectively. The best history match without any deviation between modelled and measured profiles is obtained using non-ideal model.
According to the reservoir cooling and heating from shale layers above and below the flooded sand interval, the temperature of the fluids near-wellbore will change. Since the tracer bank is injected with lower temperature than reservoir temperature, the effect of reservoir cooling on the ester partitioning coefficient is investigated in order to determine Sor more precisely. Using this numerical SWCT interpretation, it is achievable to examine other EOR methods to reach more oil recovery in this sandstone reservoir via obtained unknown parameters.
Nanoparticles (D~1 to100 nm) as part of nanotechnology have drawn the attention for its great potential of increasing oil recovery. From the authors’ previous studies, wettability alteration was proposed as one of the main Enhanced Oil Recovery (EOR) mechanisms of nanoparticles fluid. Adsorption of nanoparticles on pore wall lead to wettability alteration of reservoir. We conducted a series of wettability measurement experiments with water, neutral and oil wet core plugs, where we systematically varied nanoparticles concentration and size of nanoparticles. Nanoparticles transport experiments were also performed for three different wettability core plugs with varying flow rate, injection pattern as well as concentration and size of nanoparticles. Effluent nanoparticles concentration was measured to evaluate nanoparticles adsorption and retention in the core and also desorption during water post-flushes afterwards. Both silica hydrophilic nano-structure particles and colloidal nanoparticles were utilized in above two experiments.
The results of wettability alteration experiments indicated that hydrophilic nanoparticles have ability of making the cores to more water wet, especially for neutral and oil wet cores. Concentration and size of nanoparticles have significant effect during wettability alteration process. For nanoparticles transport experiments, the results showed that the nanoparticles undergo both adsorption and desorption as well as retention during injection. Effluent nanoparticles concentration curves were plotted to find the breakthrough time. Experiments with varying concentration, particle size and flow rate yield magnitude of nanoparticles adsorption and desorption ability for Berea sandstone. Porosity and permeability impairment were observed during nanoparticles dispersion injection.
To reduce CPU time in compositional reservoir simulations, a minimum number of components should be used in the equation of state (EOS) to describe the fluid phase and volumetric behavior. A “detailed” EOS model often contains from 20 to 40 components, with the first 10 components representing pure compounds H2S, CO2, N2, C1, C2, C3, i-C4, n-C4, i-C5, and n-C5. The remaining components represent a split of the heavier C6+ material in single-carbon-number (SCN) fractions such as C6, C7, C8 and C9, or groups of SCN fractions such as C10-C12, C13-C19, C20-C29, and C30+. Occasionally the light aromatics BTX (benzene, toluene, and xylene isomers) are also kept as separate components for process modeling. Today’s typical laboratory compositional analysis provides 50-60 components, including isomers with carbon numbers 6 to 10, SCN fractions out to C35 and a residual C36+. This is in contrast to the 11-12 components (through C7+) reported in most commercial laboratory reports pre-1980.
A “pseudoized” EOS model might contain only 6-9 lumped components – e.g. lumping “similar” components such N2+C1, i-C4+n-C4+i-C5+n-C5, and some 3-5 C6+ fractions. The selection of which components to lump together is difficult because of the huge number of possible combinations. This paper describes a systematic, automated method to search a vast number of feasible pseudoized EOS models based on an initial, detailed EOS model.
The obvious application of pseudoized EOS models is compositional reservoir simulation, where run time is an important issue and fewer components may be important. The method we present is based on (1) quantifying the “quality of match” between a pseudoized EOS model and the detailed EOS model from which it is derived, and (2) systematically testing all plausible lumping combinations. The method allows for a set of constraints to be imposed on the lumping of components, such as (1) not lumping certain non-hydrocarbons (e.g. CO2), (2) forcing the first plus fraction to contain a specific carbon-number component (e.g. C6), and (3) the last component in the original EOS not being lumped with other heavy fractions (e.g. C30+).
The proposed pseudoization procedure is comprehensive, and founded in the ability of an EOS with fewer components to describe a wide range of phase and volumetric properties covering all of the relevant pressure-temperature-composition (p-T-z) space expected for a given reservoir development. The litmus test of quality is how well the pseudoized EOS compares with the detailed EOS model from which it is derived, an EOS that accurately describes all key measured laboratory PVT data. The method proposed will find an optimal pseudoized EOS model to describe all PVT data that are relevant to a particular reservoir development – e.g. depletion performance, immiscible and miscible gas injection, compositional variation, and surface processing.
EOS-based compositional modeling is used to simulate reservoirs, production flow lines, compressors, and surface processes. Some of these models require large CPU time (hours or days), mainly reservoir models and transient flowline models. Multi-well gathering pipeline systems can also require substantial CPU time, particularly if they are connected upstream to a reservoir simulation model.
The development of current technology has enabled manufacturer to create various types of nanoparticles for multi-purposes in various sectors including the oil and gas industry. The use of nanoparticles for enhanced oil recovery (EOR) has been studied in the past decade both in the lab- and pilot-scale projects. Most of the research observed that nanoparticles are very attractive for EOR purposes. However, most of those studies use ??of silica-based nanoparticles. The use of other types of nanoparticles should be investigated as alternative solution.
In this study, two water-based metal-oxides nanoparticles: Al2O3 and TiO2, were employed. The primary size of both nanoparticles ranged of 40-60 nm. Nanofluids was prepared by dispersing 0.05 wt.% metal-oxides nanoparticles with synthetic saline water. Berea sandstones cores are used as porous media with average porosity and permeability of 15% and 60 mD respectively.
Coreflood experiment was conducted by injecting metal-oxides nanofluids as tertiary process (Nano-EOR). Degassed crude oil with viscosity ranged 5-50 cP was also used. To investigate the effect of temperature and rock wettability to oil recovery, coreflood experiment has been performed on various temperature condition and initial cores wettability: water-wet, intermediate-wet and oil-wet.
The detailed process and results are outlined in the paper to reveal the possible application of metal-oxides nanoparticles as alternative EOR method.
Ytrehus, Jan David (SINTEF Petroleum Research) | Carlsen, Inge Manfred (SINTEF Petroleum Research) | Melchiorsen, Jens Christian (Dong Energy) | Abdollahi, Jafar (Statoil ASA) | Skalle, Pal (Norwegian University of Science & Tech) | Saasen, Arild (Det Norske Oljeselskap ASA) | Taghipour, Mohammad Ali (SINTEF Petroleum Research) | Reyes, Angel (BG-Group) | Opedal, Nils Van Der Tuuk (SINTEF Petroleum Research) | Lund, Bjornar (SINTEF Petroleum Research)
Copyright 2013, SPE/IADC Middle East Drilling Technology Conference and Exhibition This paper was prepared for presentation at the SPE/IADC Middle East Drilling Technology Conference and Exhibition held in Dubai, UAE, 7-9 October 2013. This paper was selected for presentation by an SPE/IADC program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers or the International Association of Drilling Contractors and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers or the International Association of Drilling Contractors, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers or the International Association of Drilling Contractors is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE/IADC copyright.
Align with current dynamic technology development, waterflooding techniques have been improved and optimized to have better oil recovery performance. In addition the latest worldwide industries innovation trends are miniaturization and nanotechnology materials such as nanoparticles. Hence one of the ideas is using nanoparticles to assist waterflood performance. However it is crucial to have a clear depiction of some parameters that may influences displacement process.
The focus of this study is to investigate the effects of some parameters influencing oil recovery process due to nanoparticles such as particle size, rock permeability, initial rock wettability, injection rate and temperature. This study is part of our ongoing research in developing nanofluids for future or alternative enhanced oil recovery (Nano-EOR) method.
Three different sizes of hydrophilic silica nanoparticles with single particle diameter range from 7 to 40 nm were employed and have been characterized under scanning electron microscope (SEM). Nanofluids were synthesized using 0.05 wt.% nanoparticles that dispersed into synthetic brine (NaCl 3 wt.% ~ 30,000 ppm). The contact angle variation due to nanoparticles size was also measured at room condition. Coreflood experiment has been conducted using 26 Berea sandstone cores to evaluate the effect of those parameters above on oil recovery due to Nano-EOR. The cores permeability was in range from 5 to 450 mD. To study the effect of initial rock wettability on oil recovery due to Nano-EOR, original core wettability has been changed with aging process from water-wet to intermediate and oil-wet respectively. Temperature was also studied in range 25-80 oC to fulfill the possibility of applying Nano-EOR at reservoir temperature.
The coreflood testing was repeated for each case to have consistency result. The processes and results are outlined and also further detailed in the paper to bring knowledge about nanoparticles flooding as a future promising EOR method.
Hendraningrat, Luky (Norwegian University of Science & Tech)
The paper presents compositional simulation studies of miscible water-alternating-gas (WAG) flooding in stratified reservoirs with respect to compositional variation with vertical depth and temperature. Two series of fluid system were selected from fifth and third SPE comparative study for Reservoir-A and Reservoir-B respectively. The Reservoir-A is an undersaturated black oil reservoir and has initial gas-oil ratio (GOR) of 557 scf/stb. Meanwhile Reservoir-B is near-critical oil reservoir with initial GOR of 3519 scf/stb. The minimum miscible pressure (MMP) variation with depth was calculated using equation of state in both reservoirs. In this study, temperature gradient sensitivity is ranging from 10 to 30 oF per 1000 ft for both active and passive thermal gradient.
The existence of thermal diffusion in WAG process is also discussed. It is investigated that active and passive thermal gradient will give opposite composition variation trend. In active temperature gradient, the amount of light components will increase and heavy components will opposite with respect to depth. Unlike active thermal gradient, the gravity isothermal and passive thermal gradients segregate the heavy components toward the bottom.
The initial oil in place (IOIP) varies due to compositional variation which is again due to gravity and thermal gradients. These issues should be even more obvious when we have oil reservoir with higher GOR or near-critical reservoir. In these particular reservoirs, the presence of gravity and passive thermal gradients will decrease IOIP calculation whereas both reservoirs will have less C7+ components than in basecase. Otherwise, considering thermal diffusion effect by applying active thermal gradients will increase IOIP.
Several parameters were also evaluated during WAG process in both reservoirs such as: various hydrocarbon injection gases, cyclic injection scheme, WAG cycle and ratio, and reservoir heterogeneities. Therefore the effect of compositional variation due to gravity and thermal gradients can be conclusively evaluated.
Current global demand for fossil fuel such as oil is still high. This encourages oil and gas industries to improve their effort of finding new discoveries, developing technique and maximizing recovery of their current resources including in low-permeability reservoir. Enhanced oil recovery (EOR) is a technique to enhanced ultimate recovery. Since technology has been continuously developed such as nanotechnology/nano-size material, EOR methods have improved. One of them is Nano-EOR that triggered great attention in last decade. Nanoparticles may alter the reservoir fluid composition and rock-fluid properties to assist in mobilizing trapped oil. Most of observation from lab-scale reported that it seems potentially interesting for EOR.
Since reservoir management is very essential for the success of all improved/enhanced oil recovery (IOR/EOR) methods, optimizing nanofluids concentration is a proposed reservoir management to maximize oil recovery using Nano-EOR in this paper. Low-permeability water-wet Berea sandstones core-plugs with porosity ranged 13-15% and permeability ranged 5-20 mD were tested. A hydrophilic silica nanoparticles with primary particle size 7 nm was employed without surface treatment. Nanofluids with various concentration ranged 0.01 - 0.1 wt.% were synthesized with synthetic saline water for optimizing study. The wettability alteration due to nanofluids was observed; coreflood experiment was conducted and compared its displacement efficiency.
The results observed a range of nanofluids concentration that could maximize oil recovery in low-permeability water-wet Berea sandstone. Although contact angle of aqueous phase decreases as nanofluids concentration increase which means easier of oil to be released but we observed that higher concentration (e.g. 0.1 wt.%) has a tendency to block pore network and will decrease or even without additional oil recovery.
This study provides if concentration of nanofluids has an important parameter in Nano-EOR and could be optimized to maximize oil recovery of low-permeability water-wet Berea sandstone.
Determination of swept volume is important for evaluation of a thermal project. Thermal well testing offers a simple method to estimate the steam zone properties using pressure falloff tests. A composite reservoir model is assumed with two regions of highly contrasting fluid mobilities and the flood front as an impermeable boundary. The swept zone therefore acts as a closed reservoir and pressure response is characterized by pseudo steady state behavior.
Most of the previous studies have considered vertical wells because of the simpler method of well test analysis compared to horizontal wells. However, a steam assisted gravity drainage (SAGD) process using horizontal well pairs is a promising technique in heavy oil recovery.
The applicability of thermal well test analysis in estimating the swept zone properties for vertical and horizontal wells was thoroughly investigated in this study. A thermal simulator was used to simulate pressure falloff tests. The generated pressure data were then analyzed to calculate swept volume and reservoir parameters. Properties of an Athabasca heavy oil sample, measured in the lab, were used as input for numerical simulation purposes.
Results of this work show good agreement between the calculated and simulated values of swept volume, swept zone permeability and skin factor for both vertical and horizontal wells. Estimations depend on the vertical position of the pressure gauge. Effects of gravity, swept region shape, dip, steam quality, steam injection rate, injection time, permeability anisotropy and gridblock density on the results were also investigated. Higher injection rates and longer injection times lead to poorer estimates of the swept volume because of a more irregular shape of the swept region and the possibility of earlier breakthrough. Vertical and lateral distances between the horizontal injector and producer affect the estimation of swept volume. Isotropy and grid refinement do not necessarily improve the estimations.
This paper describes a systematic approach to model the phase behavior and viscosity of Athabasca bitumen and light-solvent mixtures for a wide range of temperatures. A cubic equation of state (EOS) is first developed using Athabasca crude assay data. We use a modified Jacoby correlation to describe the relationship of specific gravity and molecular weight for the bitumen sample. A gamma molar distribution model is used to fit the Athabasca crude assay data, then single-carbon-number (SCN) fractions are defined out to C90+. The Twu correlation is used for estimating SCN critical properties, including C90+, resulting in an EOS with 89 components (EOSSCN).
Pure solvent-crude oil mixture PVT data were tuned to the EOSSCN model by adjusting a fixed set of BIPs (binary interaction parameters) between pure solvent components (N2, CO, CO2, C1, C2) and all C7+ components.
For viscosity modeling, the LBC (Lorenz-Bray-Clark) correlation is used, with SCN critical volumes modified individually to ensure that the LBC correlation estimates SCN viscosities as given by a modified Twu correlation, based on specific gravity and normal boiling point.
The EOSSCN model was lumped into five pseudo-fractions (EOS5), the heaviest being C90+. The resulting model reproduces accurately all phase and volumetric behavior of pure-solvent-crude mixtures.
Initial viscosity prediction of the Athabasca crude by the EOSSCN/LBC and EOS5/LBC models is satisfactory for dead-bitumen with viscosity only affected by temperature. However, for viscosities of pure-solvent-saturated bitumen at varying temperatures, the EOS5/LBC model did not perform well. Our solution was to split the heaviest fraction C90+ into two sub-fractions, where only critical volumes differ, resulting in "lower-viscous?? and "higher-viscous?? C90+ fractions (C90+L into C90+H). The fraction of C90+L (fL) was found to correlate with pure solvent solubility and temperature, resulting in a quite-accurate overall viscosity fit. This final model has, in reality, six components, even though the two heaviest fractions are identical for EOS calculations - we call this final model EOS6/LBC.
The final EOS6/LBC model was checked against measured PVT and viscosity data for mixtures of the same Athabasca bitumen using synthetic combustion gas solvents made up of C1, CO2, and N2.