An Improved Model to Simulate Mud (Drilling Fluid) Dispersion through Porous Media

ABSTRACT: An improved model of mud dispersion has been introduced in this work (Civan and Engler, 1994; Donaldson and Chernoglazov, 1987) , this model uses more reasonable data and assumptions making it closer to real conditions

Effects of pH and Temperature on Oilfield Scale Formation

Water flooding is one of the most influential methods for pressure maintenance and enhanced oil recovery. However, water flooding is likely to develop the formation of oilfield scale. Scale formation in reservoirs, due to the mixing of injection water and formation water, could cause formation damage and production limit. Therefore, it is necessary to simulate the compatibility of brine and injection water. Scale prediction is performed using many thermodynamic and/or kinetic based models. In this study, simulations with speciation (ion pairing) are studied, which is a thermodynamic based tool. The utilization of reservoir conditions, formation water analysis, and sea water analysis as the inputs in this method resulted to the accurate prediction of potential scales. In this study, the factors impacting on the scale potential such as pH, temperature, and mixing ratio were also investigated. The obtained results showed that calcite and aragonite were the major scale potential to precipitate. Finally, the results illustrated the important effect of pH and temperature on different scales formation

Synergistic efficiency of zinc oxide/montmorillonite nanocomposites and a new derived saponin in liquid/liquid/solid interface-included systems: Application in nanotechnology-assisted enhanced oil recovery

Oil production faces challenges such as limited oil production from carbonate reservoirs, high oil production costs, and environmental issues. Chemical flooding as an enhanced oil recovery (EOR) method (CEOR) can increase oil production by the use of chemical additives such as surfactants into the reservoirs. Surfactants can increase oil recovery by interfacial tension (IFT) reduction and alteration of the rock wettability from oil-wet to water-wet. The synthesis of chemicals such as synthetic surfactants is usually costly and harmful to the environment. To solve these problems, many researchers have oriented on the use of natural surfactants instead of synthetic ones within the CEOR process. A new approach to increase the efficiency of CEOR is the synergizing of the chemical additives with nanoparticles as a hybrid fluid, which is known as the nanotechnology-assisted EOR method. In this research, a natural surfactant derived from Cyclamen persicum (CP) plant was extracted, and its performance was optimized with the zinc oxide/montmorillonite (ZnO/MMT) nanocomposite in a synergistic usage. At the optimum concentration of the surfactant, the measurements of the IFT and the contact angle show 57.78 and 61.58 % optimizations, respectively. Also, in the presence of NaCl, the performance of CP is improved. IFT and contact angle measurements were also conducted for ZnO/MMT nanofluids and CP-ZnO/MMT as hybrid nanofluids. Results indicate that ZnO/MMT nanocomposites can alter the wettability of the carbonate rock to the water-wet state. Also, the CP-ZnO/MMT hybrid nanofluid shows a good potential in both IFT reduction and altering wettability from oil-wet to water-wet. Finally, to investigate the effects of solutions on increasing oil recovery factor (RF), the optimum concentrations of the surfactant, nanocomposite, and hybrid solutions were selected for dynamic core flooding experiments, and improvements showed oil RF increases of 8.2, 6, and 13 %, respectively

Development of a fuzzy system model for candidate-well selection for hydraulic fracturing in a carbonate reservoir

With current technology, it is only possible to extract 20% to 25% of the original oil in place from Iranian carbonate reservoirs, 10% less than the world average. In addition, formation damage is a serious problem in those reservoirs, which mainly caused by asphaltene precipitation, sand production, and ineffective stimulation method. The majority of mature carbonate reservoirs in Iran have low permeability and high skin values. Therefore, such reservoirs are capable of producing at commercial rates only if they are hydraulically fractured. Acid fracturing is usually reported as a standard method for fracturing in carbonate reservoirs. Hydraulic Fracturing (HF) technology, which was originally applied to overcome near wellbore damage, is a proper replacement stimulation method. It is evident that to adopt this technology, considerable efforts have to be strenuous in candidate-well selection. As asserted in the literature, even though a common practice, candidate-well selection is not a straightforward process and up to now, there has not been a well-defined approach to address this process. The techniques applied in HF candidate-well selection could be divided into two methods; conventional and advanced approaches. Conventional methods are not easy to use for nonlinear processes, such as candidate-well selection that goes through a group of parameters having different attributes and features such as geological aspect, reservoir and fluid characteristics, production details, etc. and that's because it is difficult to describe properly all their nonlinearities. However, it is believed that advanced methods such as Fuzzy Logic (FL) could be better decrease the uncertainty existed in candidate-well selection. This paper presents a Mamdani fuzzy model where rules for HF candidate-well selection were derived from multiple knowledge sources such as existing literature, intuition of expert opinion to verify the gathered information. The needs for adapting HF as replacement stimulation in Iranina carbonate reservoirs are discussed and advanced methods for HF candidate selection will be reviewed in this paper. Also, the main reasons which show why propped HF is the choice in carbonate reservoirs will be discussed. Finally, the proposed Fuzzy system model is applied along with a case study in a carbonate reservoir

A review on conventional candidate-well selection for hydraulic fracturing in oil and gas wells

Hydraulic Fracturing (HF) which is an ever-increasing focus area for upstream industry is the pumping of fluids at high rates and pressures in order to break the rock, and it is using to accelerate hydrocarbon production and improving ultimate recovery in many reservoirs. It is clearly indicated in HF experience's literature, to be successful conducted, it is directly depending on rigorous candidate-well selection. The techniques applied in HF candidate-well selection could be divided into two methods; conventional and advanced approaches. Being familiar with the conventional methods in candidate-well selection that mainly deals with engineering, geological, etc aspects in decision making process, is of particular importance in order to increase the performance of the advanced techniques that mainly utilized artificial intelligence methods. This paper is a review of the conventional candidate-well selection for hydraulic fracturing in oil and gas wells