Tar mats at the oil-water contact (OWC tar mats) in oilfield reservoirs can have enormous, pernicious effects on production due to possibly preventing of any natural water drive and precluding any effectiveness of water injectors into aquifers. In spite of this potentially huge impact, tar mat formation is only now being resolved and integrated within advanced asphaltene science. Herein, we describe a very different type of tar mat which we refer to as a "rapid-destabilization tar mat??; it is the asphaltenes that undergo rapid destabilization. To our knowledge, this is the first paper to describe such rapid-destabilization tar mats at least in this context. Rapid-destabilization tar mats can be formed at the crest of the reservoir, generally not at the OWC and can introduce their own set of problems in production. Most importantly, rapid-destabilization tar mats can be porous and permeable, unlike the OWC tar mats. The rapid-destabilization tar mat can undergo plastic flow under standard production conditions rather unlike the OWC tar mat. As its name implies, the rapid-destabilization tar mat can form in very young reservoirs in which thermodynamic disequilibrium in the oil column prevails, while the OWC tar mats generally take longer (geologic) time to form and are often associated with thermodynamically equilibrated oil columns. Here, we describe extensive data sets on rapid-destabilization tar mats in two adjacent reservoirs. The surprising properties of these rapid-destabilization tar mats are redundantly confirmed in many different ways. All components of the processes forming rapid-destabilization tar mats are shown to be consistent with powerful new developments in asphaltene science, specifically with the development of the first equation of state for asphaltene gradients, the Flory-Huggins-Zuo Equation, which has been enabled by the resolution of asphaltene nanostructures in crude oil codified in the Yen-Mullins Model. Rapid-destabilization tar mats represent one extreme while the OWC tar mats represent the polar opposite extreme. In the future, occurrences of tar in reservoirs can be better understood within the context of these two end members tar mats. In addition, two reservoirs in the same minibasin show the same behavior. This important observation allows fluid analysis in wells in one reservoir to indicate likely issues in other reservoirs in the same basin.
A Jurassic oil field in Saudi Arabia is characterized by black oil in the crest, with heavy oil underneath and all underlain by a tar mat at the oil-water contact (OWC). The viscosities in the black oil section of the column are similar throughout the field and are quite manageable from a production standpoint. In contrast, the mobile heavy oil section of the column contains a large, continuous increase in asphaltene content with increasing depth extending to the tar mat. Both the excessive viscosity of the heavy oil and the existence of the tar mat represent major, distinct challenges in oil production. A simple new formalism, the Flory-Huggins-Zuo (FHZ) Equation of State (EoS) incorporating the Yen-Mullins model of asphaltene nanoscience, is shown to account for the asphaltene content variation in the mobile heavy oil section. Detailed analysis of the tar mat shows significant nonmonotonic content of asphaltenes with depth, differing from that of the heavy oil. While the general concept of asphaltene gravitational accumulation to form the tar mat does apply, other complexities preclude simple monotonic behavior. Indeed, within small vertical distances (5 ft) the asphaltene content can decrease by 20% absolute with depth. These complexities likely involve a phase transition when the asphaltene concentration exceeds 35%. Traditional thermodynamic models of heavy oils and asphaltene gradients are known to fail dramatically. Many have ascribed this failure to some sort of chemical variation of asphaltenes with depth; the idea being that if the models fail it must be due to the asphaltenes. Our new simple formalism shows that thermodynamic modeling of heavy oil and asphaltene gradients can be successful. Our simple model demands that the asphaltenes are the same, top to bottom. The analysis of the sulfur chemistry of these asphaltenes by X-ray spectroscopy at the synchrotron at the Argonne National Laboratory shows that there is almost no variation of the sulfur through the hydrocarbon column. Sulfur is one of the most sensitive elements in asphaltenes to demark variation. Likewise, saturates, araomatics, resins and asphaltenes (SARA); measurements also support the application of this new asphaltene formalism. Consequently, the asphaltenes are very similar, and our new FHZ EoS with the Yen-Mullins formalism properly accounts for heavy oil and asphaltene gradients.
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.
Viscosity and Density are important physical parameter of crude oil, closely related with the whole processes of production and transportation, and are very essential properties to the process design and petroleum industries simulation. As viscosity increases, a conventional measurement becomes progressively less accurate and more difficult to obtain. According to the literature survey, most published correlations that are used to predict density and viscosity of heavy crude oil are limited to certain temperatures, API values, and viscosity ranges. The objective of present work is to propose accurate models that can successfully predict two important fluid properties, viscosity and density covering a wide range of temperatures, API, and viscosities. Viscosity and density of more than 30 heavy oil samples of different API gravities collected from different oilfield were measured at temperature range 15oC to 160oC (60oF to 320oF), and the results were used to ensure the capability of proposed and published correlations to predict the experimental viscosity and density data. The proposed correlation can be summarized in two stages. The first step was to predict the heavy oil density from API and temperature for different crudes. The predicted values of the densities were used in the second step to develop the viscosity correlation model. A comparison of the predicted and actual viscosities data, concluded that the proposed model has successfully predict all data with average relative errors of less than 12% and with the correlation coefficient R2 of 0.97, and 0.92 at normal and high temperatures respectively. Meanwhile, the results of most of the available models has an average relative error above 40%, with R2 values between 0.19 to 0.95. These comparisons were made as a quality control to confirm the reliability of the proposed model to predict density and viscosity values of heavy crudes when compared with other models.
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 North Kuwait Jurassic Gas (NKJG) reservoirs are currently under development by KOC. The fractured carbonate reservoirs contain gas condensate and volatile oil at pressures up to 11,500 psi with 2.9% H2S and 1.5% CO2. Currently around 20 active wells are producing to an Early Production Facility (EPF-50) that falls short of achieving the desired capacity and capability to handle production efficiently.
To understand wells and field performance, an integrated system model comprising of wells, flow line and gathering system separator network was created. The setting up a model and its use is an integral subset of WRFM (Wells, Reservoir and Facilities Management) process that is essential for effectively managing the current asset and for further field development.
The application of the model is to be an enabler for wider implementation of the WRFM process in KOC and a tool to meet the following objectives:
The model has shown close approximation with field metered production and is already achieving many of its desired objectives.
This paper describes the use of integrated nodal analysis model to generate data gathering and well intervention opportunities not only to operate the facilities efficiently but understand well and reservoir behavior for input to full field development plan.
Exploration activity during the last ten years, targeting Jurassic carbonate reservoirs in North Kuwait (Fig 1), has culminated in the discovery of six major tight gas condensate fields, encompassing an area of about 1,800 sq km with a reservoir gross thickness of about 2,200 ft. These fields are the first free-gas fields in Kuwait, which were put on early production during 2008. The reservoirs are characterized with dual porosity matrix system, dominated by low porosity and permeability, in deep HP/HT conditions, with wide variety of hydrocarbon fluids ranging from volatile oil to gas condensate with sour gas. Typical per well production rates are up to 5,000 BOPD/BCPD and 10 MMSCFPD, making them an excellent commercial success.
Khan, M. Noman (Pakistan Petroleum Limited) | Bilal, Hafiz M. (NED University of Engineering & Technology) | Shoaib, M. (NED University of Engineering & Technology) | Manzoor, Abdul-Ahad (NED University of Engineering & Technology) | Shaukat, Wasif (NED University of Engineering & Technology) | Shakil, Talha (NED University of Engineering & Technology)
Correct selection of Equation of State (EOS) model is required for proper fluid characterization of retrograde gas condensate fluid so that PVT behavior in the simulation model can be correctly defined. This paper describes the methodology used for establishing the criteria for selecting the most representative PVT laboratory analysis when several PVT analyses are available. The steps for Equation of State (EOS) modeling from the selected PVT report of a retrograde gas condensate fluid sample, which will be used in compositional reservoir simulation model, are also presented in the paper.
One of the important steps in the proposed methodology is to examine the available PVT analysis results for accuracy, consistency and validity. The Whitson Torp (K-value flash) method which is based on mass balance has been used for evaluating experimental data by calculating percentage difference between reported values and calculated values of oil composition, molecular weight of C7+ and specific gravity of C7+ at abandonment pressure. EOS models have been developed using two well- known PVT analyses software. Three parameter Peng-Robinson EOS was selected for EOS modeling. The EOS model was tuned by regressing the Binary Interaction Coefficients and other critical properties of pseudo components. After regression, the fluid composition was lumped into five components to reduce simulation time while preserving the inherent nature of the EOS model. The developed EOS model has been used for material balance and simulation studies.
A proper analysis and characterization of the reservoir fluid is the most important step in successful application of a compositional model to determine the fluid behavior and properties.
This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 148717, "Effects of Fluid and Rock Properties on Reserves Estimation," by Kegang Ling, SPE, Zheng Shen, SPE, Texas A&M University, prepared for the 2011 SPE Eastern Regional Meeting, Columbus, Ohio, 17-19 August. The paper has not been peer reviewed.
Simple methods, such as the use of density during compositional simulations, often fail to identify the phases correctly, and this can cause discontinuities in the computed relative permeability values. The results are then physically incorrect. Furthermore, numerical simulators often slow down or even stop because of discontinuities. There are many important applications in which the phase behavior can be single phase, gas/liquid, liquid/liquid, gas/liquid/liquid, or gas/liquid/solid at different times in different gridblocks. Assigning physically correct phase identities during a compositional simulation turns out to be a difficult problem that has resisted a general solution for decades. We know that the intensive thermodynamic properties, such as molar Gibbs free energy, must be continuous, assuming local equilibrium, but this condition is difficult to impose in numerical simulators because of the discrete nature of the calculations. An alternative approach is to develop a relative permeability model that is continuous and independent of the phase numbers assigned by the flash calculation. Relative permeability is a function of saturation, but also composition, because composition affects the phase distribution in the pores (i.e., the wettability). The equilibrium distribution of fluids in pores corresponds to the minimum in the Gibbs free energy for the entire fluid/rock system, including interfaces. In general, however, this relationship is difficult to model from first principles. What we can easily do is calculate the molar Gibbs free energy (G) of each phase at reference compositions where the relative permeabilities are known or assumed to be known and then interpolate between these values by use of the G calculated during each timestep of the simulation. Relative permeability values calculated this way are unconditionally continuous for all possible phase-behavior changes, including even critical points. We tested the new relative permeability model on a variety of extremely difficult simulation problems with up to four phases, and it has not failed yet. We illustrate several of these applications.