The oil-water interfacial tension (IFT) is by all means important in capillary pressure estimation and fluid-fluid and fluid-rock interactions analysis. Observations from experimental data indicate that oil-water IFT is a function of pressure, temperature, and compositions of oil and water. A reliable correlation to estimate oil-water IFT is highly desire. Unfortunately to our best knowledge no correlation that uses the compositions of oil and water as inputs is available. Our work is to fill this gap.
In this research, we collected data from former studies and investigations and developed a correlation for oil-water IFT. In the proposed correlation oil-water IFT is a function of system pressure, temperature, and compositions of oil and water. Error analysis was conducted to check the accuracy of the equation by comparing the calculated values with the experimental data. The results indicated that the new correlation predicts reliable oil-water IFTs. Our correlation calculates the oil-water IFT from system pressure, temperature, and compositions of oil and water. It addresses the effect of composition of oil on IFT, which is not presented in existing correlations. Therefore it can not only be applied in the calculation of capillary pressure in the compositional simulation, but also be used in daily petroleum engineering calculation such as waterflooding analysis.
Significant advances have been made in formation testing since the introduction of wireline pumpout testers (WLPT), particularly with respect to downhole fluid compositional measurements. Optical sensors and the use of spectroscopic methods have been developed to improve sample quality and minimize sampling time in downhole environments. As a laboratory technique, spectroscopy is a ubiquitous and powerful technology that has been used worldwide for decades to measure the physical and chemical properties of many materials, including petroleum, geological, and hydrological samples. However, laboratory-grade, high-resolution spectrometers are incompatible with the hostile environments encountered downhole, at wellheads, and on pipelines. Only limited resolution techniques are available for the rugged conditions of the oil field. This paper introduces a new optical technology that can provide high-resolution, laboratory-quality analyses in harsh oilfield environments.
A new technology for optical sensing, multivariate optical computing (MOC), has been developed and is a non-spectroscopic technique. This new sensing method uses an integrated computation element (ICE) to combine the power and accuracy of high-resolution, laboratory-quality spectrometers with the ruggedness and simplicity of photometers. Many modern sensors typically merge the sensor with the electronics on an integrated computing chip to perform complex computations, resulting in an elegant yet simplistic design. Now, optical sensing using ICE features an analogue optical computation device to provide a direct, simple, and powerful mathematical computation on the optical information, completely within the optical domain. Because the entire optical range of interest is used without dispersing the light spectrum, the measurements are obtained instantly and rival laboratory-quality results.
A proof of concept MOC with ICE has been demonstrated, logging more than 7,000 hours, in nearly continuous use for 14 months. Oils with gravities ranging from 14 to 65°API have been measured in downhole environments that range from 3,000 to 20,000 psi, and from 150 to 350°F. Hydrocarbon composition measurements, including saturates, aromatics, resins, asphaltenes, methane, and ethane, have been demonstrated using the MOC configuration. As compositional calculations therein, GOR and density are validated to within 14 scf/bbl and 1%, respectively. The paper discusses the details of the new ICE-based sensor and describes its adaptations to downhole applications.
The matrix blocks in fractured reservoirs are the primary storage of hydrocarbons, so matrix-fracture transfer mechanisms are of crucial importance in recovery from fractured reservoirs. During gas injection into fractured reservoirs, fractures are filled with injected gas while matrix blocks contain the reservoir fluid. In this condition due to compositional difference between the gas in fractures and the fluid in matrix, diffusive exchanges of components between matrix and fracture may have significant contribution on matrix oil recovery in addition to gravity drainage or other transfer mechanisms.
In this work, to evaluate the significance of molecular diffusion, the laboratory experiment of "Gas Injection into Fractured cores?? is simulated using a compositional model and this model is used to run several experiments which help in understanding the way that each recovery mechanism acts. The advantage of running simulation in core scale is that in this way there is the possibility of using small grid size which significantly reduces the issues of numerical dispersion. And more over the existing experimental data can be used for model adjustment. In the experimental works the procedure is to place a core sample into a core holder in such a way that the annulus space between the core boundary and the core holder is very small. This annulus space is representative of the fracture surrounding the matrix blocks in the reservoir. Then after using special techniques the core is saturated with the representative reservoir oil, and after this primary core initialization, gas is injected into the annulus and the amount of recovered oil is measured versus time.
This study reveals that, molecular diffusion acts like a catalyst and improves the recovery mechanism by enhancing the gas movement within matrix. At the prevalent conditions of this work, the main recovery mechanisms are the miscibility effects (Condensing or Vaporizing gas drives) that are enhanced by molecular diffusion. Sensitivity analysis done in this work reveals that significance and contribution of molecular diffusion in recovery changes with different parameters such as matrix permeability and porosity, gas composition, etc.
Fractured reservoirs contain a significant portion of the world's reserves, and Gas injection is a common recovery practice in these reservoirs and understanding the recovery mechanisms is of crucial importance for correct simulation of this process. This study shows, although significance of molecular diffusion changes with reservoir parameters, any way neglecting it in simulation studies will result in underestimation of gas injection efficiency.
In light of the recent increasing interest in the oil and gas developmentsin the arctic region, Huisman Equipment B.V. has developed a Mobile OffshoreDrilling Unit (MODU) named JBF Arctic suited for arctic condition. The stationkeeping in ice is one of the crucial factors determining the feasibility of thedesign. As one of the first steps of the design process ice model tests wereperformed at the Krylov Shipbuilding Research Institute (KSRI) to gain insightin the ice forces acting on the unit. During the model tests the model of theJBF Arctic was retained in a fixed position while being towed through the ice.In reality the station keeping of the unit will be ensured by a mooring system,which has certain flexibility compared to the rigid constrains in the modeltests. This paper elaborates on the creation of a numerical model that canperform time-domain simulations of the dynamic interaction between the vesseland the ice-loads. Using these simulations the mooring system is optimized inorder to cope with the ice loads corresponding to unbroken level ice withthickness up to 3.1m. Several important conclusions were drawn. One is the factthat no dominating frequencies of the ice failing could be identified from themodel tests. This can be explained by a large ratio between the diameter of theunit and the ice thickness. So the ice failure mechanism has a chaoticcharacter. Another conclusion is that the unit does not exhibit significantdynamic behavior. This means that a quasi-static approach can be generally usedfor initial design of the mooring system.
Keywords: ice model test, dynamic ice-structure interaction, ice loadingmodel, mooring system optimization, Arctic MODU.
In work principles of modeling of interaction of sea gravitational oil andgas extraction platforms with the soil basis are presented. The seabed level ispresented by the non-uniform model consisting of seven layers of soils, satedwith a liquid. Approximate calculation of interaction platform Prirazlomnayawith a sea-bottom is resulted.
Efficient and robust phase equilibrium computation has become a prerequisite for successful large-scale compositional reservoir simulation. When knowledge of the number of phases is not available, the ideal strategy for phase-split calculation is the use of stability testing. Stability testing not only establishes whether a given state is stable, but also provides good initial guess for phase-split calculation. In this research, we present a general strategy for two- and three-phase split calculations based on reliable stability testing. Our strategy includes the introduction of systematic initialization of stability testing particularly for liquid/liquid and vapor/liquid/liquid equilibria. Powerful features of the strategy are extensively tested by examples including calculation of complicated phase envelopes of hydrocarbon fluids mixed with CO2 in single-, two-, and three-phase regions.
The Microemulsion phase behavior model based on oleic-aqueous-surfactant pseudo-phase equilibrium, commonly used in chemical flooding simulators, is coupled to Gas-Oil-Water phase equilibrium in our new four-fluid-phase, fully implicit In-House Research Reservoir Simulator (IHRRS). The method consists in splitting the equilibrium in two stages, where all the components other than surfactant are equilibrated first (e.g. using a black-oil, K-value or equation of state model), and the resulting Gas, Oil and Water phases are then lumped into pseudo-phases to be equilibrated using the Microemulsion model. This subdivision in stages is conceptual, and at each converged time-step the four phases (Gas, Oil, Water and Microemulsion, when simultaneously present) will be in equilibrium with each other.
The fluid properties (such as densities, viscosities and interfacial tensions) and rock-fluid properties (such as relative permeabilities), required in the transport equations, are evaluated with models from well-known industrial or academic simulators. Surfactant flooding being usually implemented as a tertiary recovery mechanism, on fields for which complete models that we do not wish to modify already exist, particular care is devoted to ensuring continuity of the physics at the onset of surfactant injection.
Our code is validated against a reference academic chemical flooding simulator, on 1D corefloods where the original hydrocarbons in place form a dead-Oil phase, possibly with free dry-Gas. Some numerical aspects of our implementation such as numerical dispersion versus time-step size and nonlinear convergence performance are also discussed. As an application example of our code where it is necessary to account for four phases in equilibrium, we consider a scenario where the chemical flood is preceded by a vaporizing Gas drive.
Surfactant flooding, whose key principle is to improve pore-level sweep efficiency by reducing the interfacial tension between injected Water and reservoir Oil (Lake, 1989), recently received renewed attention due to the perspective of long-lasting high oil prices. Meaningful simulation of surfactant flooding is challenging, in particular because when the surfactant concentration in the Water phase goes above a Critical Micelle Concentration (CMC), Water and Oil become mutually soluble in a proportion mainly determined by water salinity CS. Three different phase environments should be considered (Nelson & Pope, 1978; Lake, 1989). Near the so-called optimal salinity CSOP the surfactant is similarly hydrophilic and lipophilic, and a middle phase called Microemulsion forms, containing the surfactant in excess of the CMC as well as dispersed oil and water (Winsor III environment). This is the best performing regime because interfacial tensions between Water and Microemulsion and between Microemulsion and Oil are then extremely low. At low salinity the surfactant is typically hydrophilic, hence only Oil and a Microemulsion phase containing dispersed oil coexist (Winsor II- environment); on the contrary at high salinity the surfactant is typically lipophilic, hence only Water and a Microemulsion phase containing dispersed water coexist (Winsor II+ environment).
Numerical modeling of advanced recovery mechanisms at the reservoir scale (e.g. miscible or immiscible Gas flood, chemical flood, steam injection…), typically implemented in a tertiary phase, is essential to reasonably estimate their potential benefit and to rank the various field development options. In this perspective, using a unique advanced-physics simulator for the entire life of an asset is a desirable objective, because in addition to saving engineering time spent in data conversion, it ensures continuity of the models at all times. In our view such a tool, expected to be flexible and allow reactivity for testing new models, should come as a complement to optimized and robust industrial-grade simulators used for prediction and history matching during primary and secondary recovery.
In this paper we present the prototyping framework implemented in our In-House Research Reservoir Simulator (IHRRS), enabling easy integration of new physics for improved recovery processes with the well-known Black-Oil and K-value or Equation of State compositional models. As a demonstration example, we choose Surfactant-Polymer (SP) flooding, possibly requiring an additional Microemulsion phase. The framework is based on a natural variables formulation, solving a coupled system of conservation equations for the hydrocarbon and aqueous components (and optionally for the energy), simultaneously with a set of local thermodynamic constraints. These constraints enforce the equilibrium of hydrocarbon and aqueous components across the different fluid phases, including the equilibrium of Water and Oil with Microemulsion.
To ensure compatibility between the different recovery mechanisms handled by our system, as well as to facilitate their development and benchmarking, special attention has been paid to developing physical options as plug-in functionalities. For this purpose, instead of relying on complex software engineering tools we prefer the approach of using low-level interfaces to communicate between the core and the modules (such as the fluid, the petrophysical, or the surface facility modules). Most of our modules are entirely independent from each other, and can be compiled as stand-alone programs to be called by MATLAB® or Python scripts for instance; symmetrically, they could be replaced by external software in order to test third party functionalities.
As a first benchmark of our IHRRS, we consider a surfactant-polymer flood scenario in a 2D anisotropic quarter five-spot setting, and compare our solutions against those of a reference academic chemical flooding simulator (UTCHEM). The potentialities of our framework will then be demonstrated on a simplified model of a real Middle-Eastern field.
The paper presents a C7+ characterization procedure for the PC-SAFT equation of state. The characterization procedure was applied to model both routine and EOR PVT for a Middle East reservoir fluid. The injection gas contained 60 mole% of CO2. No other parameter adjustment was needed than to determine the optimum binary interaction parameters for CO2. Among the data matched was a liquid-liquid critical point on a swelling curve for a CO2 mol% of 43. The PC-SAFT simulation results suggest that the fluid for this CO2 concentration has two critical points. The one at the lower temperature agrees with the critical point found in the swelling test. The study shows that the potential of the PC-SAFT equation of state in the oil industry is not limited to modeling of asphaltene precipitation and other specialized applications. Extensive routine and EOR PVT data including a minimum miscibility pressure has been modeled using the PC-SAFT equation. Unlike cubic equations, a volume correction does not have to be applied to match liquid densities.
Dew point pressure is a critical measurement for any wet gas reservoir. Condensate blockage is likely when the reservoir pressure decreases below the dew point pressure and this can result in a reduction of gas productivity. Errors in measuring dew point pressure can lead to errors in the estimation of the onset of condensate blockage and thus be detrimental to the management of wet gas fields. This work presents experimental verification of a new method of determining dew point pressures for wet gas fluids. Results obtained from this method are compared to calculated values based on Peng Robinson equation of state.
Dew point pressure determination is important when devising solutions on how to prevent condensate blockage. One possible treatment fluid, carbon dioxide, has the ability to lower dew point pressures and thus delay the onset of condensate blockage. The novel method presented in this work was applied to determine the experimental dew point pressure of several wet gas mixtures as a function of carbon dioxide concentration. These experiments also show the potential of using carbon dioxide to lower dew point pressures in wet gas fields.
Experimental results show close match between the experimental estimates of dew point pressure and the Peng Robinson calculations. Experimental results also support the general observation that carbon dioxide has the ability to lower the dew point pressure of wet gas fields.
The results of this work are useful in Enhanced Oil/Gas Recovery processes that utilize carbon dioxide and for Huff and Puff which uses carbon dioxide to remove and prevent further build-up of condensate banks in wet gas reservoirs. This work investigates experimental conditions showing the change in dew point pressure as a function of carbon dioxide concentration. This dynamic relationship can be used to tune equation of state models which, in turn, allows more accurate reservoir modeling of hydrocarbon recovery process.