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Lotfollahi, Mohammad (University of Texas at Austin) | Farajzadeh, Rouhi (Shell Global Solutions International) | Delshad, Mojdeh (Delft University of Technology) | Al-Abri, Al-Khalil (University of Texas at Austin) | Wassing, Bart M. (Petroleum Development Oman) | Al-Mjeni, Rifaat (Petroleum Development Oman) | Awan, Kamran (Petroleum Development Oman) | Bedrikovetsky, Pavel (Petroleum Development Oman)
Polymer flooding is one of the most widely used chemical enhanced-oil-recovery (EOR) methods because of its simplicity and low cost. To achieve high oil recoveries, large quantities of polymer solution are often injected through a small wellbore. Sometimes, the economic success of the project is only feasible when injection rate is high for high-viscosity solution. However, injection of viscous polymer solutions has been a concern for the field application of polymer flooding.
The pressure increase in polymer injectors can be attributed to (1) formation of an oil bank, (2) polymer rheology (shear-thickening behavior near wellbore), and (3) plugging of the reservoir pores by insoluble polymer molecules or suspended particles in the water.
In this paper, a new model to history match field injection-rate/pressure data is proposed. The pertinent equations for deep-bed filtration and external-cake buildup in radial coordinates were coupled to the viscoelastic polymer rheology to capture important mechanisms. Radial coordinates were selected to minimize the velocity/shear-rate errors caused by gridblock size in the Cartesian coordinates.
The filtration theory was used and the field data history matched successfully. Systematic simulations were performed, and the impact of adsorption (retention), shear thickening, deep-bed filtration, and external-cake formation was investigated to explain the well-injectivity behavior of polymer. The simulation results indicate that the gradual increase in bottomhole pressure (BHP) during early times is attributed to the shear-thickening rheology at high velocities experienced by viscoelastic hydrolyzed polyacrylamide (HPAM) polymers around the wellbore and the permeability reduction caused by polymer adsorption and internal filtration of undissolved polymer. However, the linear impedance during external-cake growth is responsible for the sharper increase in injection pressure at the later times.
One can use the proposed model to calculate the injectivity of the polymer-injection wells, understand the contribution of different phenomena to the pressure rise in the wells, locate the plugging or damage that may be caused by polymer, and accordingly design the chemical stimulation if necessary.
Al-Maamari, Rashid S. (Sultan Qaboos University) | Al-Hashmi, Abdulaziz (Sultan Qaboos University) | Al-Azri, Nasser (Petroleum Development Oman) | Al-Riyami, Omaira (Petroleum Development Oman) | Al-Mjeni, Rifaat (Petroleum Development Oman) | Dupuis, Guillaume (Poweltec) | Zaitoun, Alain (Poweltec)
A Polymer Flooding pilot trial has being implemented in a heavy oil field, in the South of Oman. A joint team composed of personnel from Sultan Qaboos University, Poweltec and Petroleum Development of Oman provided full laboratory support which included polymer products screening, and core-flooding experimental tests. The reservoir under investigation is a high-permeability sandstone with oil viscosity of around 500 mPa.s, brine salinity of around 5,000 ppm TDS and a subsurface temperature of 50°C. The reservoir characteristics are within the upper boundaries of known polymer flooding applications worldwide. This is further compounded by the presence of a strong bottom aquifer drive which requires the optimization of well placement.
Laboratory work consisted of both bulk and core-flood testing, in which different commercial hydrolyzed polyacrylamides were submitted to rheology, filtration and stability tests, from which one product was qualified. An intensive coreflood program was executed, consisting of rheology, adsorption and displacement experiments. Due to mild reservoir conditions (low salinity and temperature), the main focus was on filtration quality of the products. Following on from the filtration tests, coreflooding programs were implemented with very long sequence of polymer injection at a rate representative of polymer propagation in the reservoir.
Adsorption was found to be quite low (around 20 µg/g) for all the tested products. In-situ rheology was correlatable to the viscosity trends. The program of tests finally qualified a product with molecular weight of around 20 million Dalton. Above this level, long-term filtration becomes questionable with a slow but continuous ramp up of pressure noticeable after about 50 Pore Volumes.
Al-Yaarubi, Azzan (Schlumberger) | Al-Mjeni, Rifaat (Petroleum Development Oman) | Bildstein, Joachim (Petroleum Development Oman) | Al-Ani, Khaled (Petroleum Development Oman) | Mikhasev, Maxim (Petroleum Development Oman) | Legendre, Fabienne (Schlumberger) | Hizem, Mehdi (Schlumberger)
We document the results of dielectric dispersion logging conducted in the Sultanate of Oman in wells drilled with oil-based mud. No conductive mud in the borehole complicates the tool response and requires careful job planning and the application of precise environmental corrections.
The borehole-corrected data are interpreted to deliver water-filled porosity, an estimate of salinity, a textural exponent usually designated mn, and the resistivity of the invaded zone. The invasion of oil-based mud filtrate generally displaces mobile fluid within the few inches of the tool’s depth of investigation. The water-filled porosity can then be interpreted as irreducible. By making permittivity and conductivity measurements over a wide range of frequencies and applying a dispersion model we derive a very accurate micro-resistivity log in boreholes drilled with oil-based mud. Formation water salinity and the water tortuosity factor mn can be derived from the dielectric dispersion measurements in favorable conditions.
Applications of dielectric dispersion logging in oil-based mud systems are demonstrated in various carbonate and clastics formations with known pay-evaluation challenges. The same interpretation techniques were then applied to improve the evaluation of a deep tight gas formation. The primary objectives were the determination of saturation, location of the water, and definition of intervals with mobile water. The results were compared with those from nuclear magnetic resonance and conventional formation evaluation. Overall, dielectric dispersion logging provided accurate water-filled porosity and microresistivity measurements. The interpretation of these results provided a robust distinction of gas-bearing intervals and saturation evaluation. Mud logs and well test results further supported the dielectric log interpretation.
There have been a number of major heavy oil discoveries in Oman in recentyears. In order to devise efficient and cost effective recovery mechanismcareful and detailed subsurface understanding of these fields is critical. Tothis end, petrophysical understanding plays a critical role, as it represents abasic building block of the static and dynamic models. The field under study isa fractured carbonate reservoir with high viscous oil. It is believed that thisreservoir has gone through various cycles of drainage and imbibition. Thus, inaddition to the complex geology, understanding of fluid distribution and fluidmobility are among major challenges that detailed petrophysical evaluationneeds to address. Understanding these parameters will help determine thefeasibility of the recovery methodology to be adopted.
This paper details a novel petrophysical workflow that integrates 3D NMR, multiarray/multi frequency dielectric measurements, borehole images, and coreanalysis. The core analysis focused on capillary pressures, Dean-Stark, androck typing. Fracture studies included detailed image analysis and extensivefall off test for understanding the nature and distribution of the fracturenetwork in the reservoir. The wealth of well data coupled with geological anddynamic data reduced the overall reservoir properties and fluid distributionuncertainties.
Dielectric data provided resistivity independent saturations validated byDean-Stark data. Combining dielectric and 3D NMR data allowed better formationcharacterization and fluid type evaluation and their present day distribution.Additionally, this combination indicated that water is not at an irreduciblestate in the reservoir. This was supported by the core saturation heightfunction which indicated that present day saturation should be much higher ifthe reservoir was in drainage mode. These results were crucial to evaluatedevelopment options, underlying uncertainty/risks of this reservoir, and designoptimum future data acquisition requirements.
Masalmeh, Shehadeh K. (Shell Technology Oman) | Wei, Lingli (Shell International Exploration & Production B.V.) | Hillgartner, Heiko (Petroleum Development Oman) | Al-Mjeni, Rifaat (Shell) | Blom, Carl P.A. (Shell Intl E&P)
Enhanced oil recovery (EOR) has become increasingly important to maintain and extend the production plateaus of existing oil reservoirs. Simulation models for EOR studies require the right level of spatial resolution to capture reservoir heterogeneity. Data acquired from the dedicated observation wells are essential in defining the required resolution to capture reservoir heterogeneity. For giant reservoirs with long production history, their full field models usually have grid block sizes that are of similar scale as the distance between injectors and observation wells, with the consequence of losing the value of the time lapse saturation logs from dedicated observation wells. Therefore, using high resolution sector models, especially from the part of the reservoir where static and dynamic data sets are rich, is a must.
The objective of this paper is to present an improved and integrated reservoir characterization, modelling and water and gas injection history matching procedure of a giant Cretaceous carbonate reservoir in the Middle East. The applied workflow integrates geological, petrophysical, and dynamic data in order to understand the production history and the remaining oil saturation distribution in the reservoir. Large amounts of field data, including time lapse saturation logs from observation wells, have been collected over the last decades to provide insight into the sweep efficiency and flow paths of the injected water.
Iterative simulations were performed to investigate different scenarios and various sensitivities with each iteration involving an update of the static model to honor both the dynamic and core/log data. While applying this iterative process it was also acknowledged that conventional core data (e.g. 1 plug per foot) may not capture the high permeability streaks in these heterogeneous reservoirs that control much of the reservoir flow behaviour, hence much denser plugging and core examination is required. In addition, permeability upscaling procedures need to take into account the fact that core plugs may not represent the effective permeability of the larger connected vuggy pore systems.
The improved understanding of reservoir heterogeneity, the more robust reservoir characterization, and the improved history matching demonstrates that a better representation of reservoir dynamics is achieved. This provides a solid platform for designing and planning future EOR schemes.
Carbonate reservoirs contain more than 50% of world's remaining conventional hydrocarbon reserves and on average have relatively low recovery factors. With the insight that the era of "easy oil?? (conventional oil and natural gas that are relatively easy to extract) is phasing out, enhanced oil recovery (EOR) becomes increasingly important to maintain and extend the production plateaus from existing oil reservoirs. EOR technologies, however, require a refined understanding of reservoir heterogeneities and dynamic field performance. Simulation models for EOR studies need to have the right level of resolution and details. Often, we find that for a giant reservoir with a long waterflood history, working with full field models with coarse simulation grids is not adequate to understand the reservoir performance and calibrate the static model. Therefore, using high resolution sector models, especially from the part of the reservoir where static and dynamic data sets are rich, is a must.