Application of nanotechnology by means of nanoparticles and nanodispersions in oil recovery - A comprehensive review

Viscosity of nanofluids can significantly affect pumping power, pressure drop, workability of the nanofluid as well as its convective heat transfer coefficient. Experimental measurements of this property for different nanoparticles and base fluids at various temperatures is cumbersome and expensive. In this communication, a comprehensive review of the most important modeling works on viscosity of nanofluids including theoretical models, empirical correlations, and computer-aided models is conducted. Next, four multilayer perceptron (MLP) models optimized with Levenberg-Marquardt (LM), Bayesian Regularization (BR), Scaled conjugate gradient (SCG), and Resilient Backpropagation (RB), two radial basis function (RBF) neural network models optimized with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), and one least square support vector machine (LSSVM) model optimized with coupled simulated annealing (CSA) were developed for the prediction of nanofluid viscosity based on 3144 data points. These data sets include 42 nanofluid systems under a wide range of operating conditions; including temperature from −35 to 80 °C, particle volume fraction from 0% to 10%, nanoparticle size from 4.6 to 190 nm, and viscosity of base fluid from 0.24 to 452.6 cP. Then, these seven models were combined in a single model using a committee machine intelligent system (CMIS). The proposed CMIS predicts all of the data with excellent accuracy with an average absolute relative error of less than 4%. Furthermore, the developed model was compared with five theoretical models and four empirical correlations through statistical and graphical error analyses. The results demonstrate that the proposed CMIS model significantly outperforms all of the existing models and correlations in terms of accuracy and range of validity. Finally, the quality of the experimental data was examined both graphically and statistically and the results suggested good reliability of the experimental data.

On the evaluation of the viscosity of nanofluid systems: Modeling and data assessment

The novel approach for the enhancement of rheological properties of water-based drilling fluids by using multi-walled carbon nanotube, nanosilica and glass beads

Recent advances in cellulose and its derivatives for oilfield applications.

Nanomaterials are engineered materials with at least one dimension in the range of 1–100 nm. Nanofluids—nanoscale colloidal suspensions containing various nanomaterials—have distinctive properties and offer unprecedented potential for various sectors such as the energy, cosmetic, aerospace and biomedical industries. Due to their unique physico-chemical properties, nanoparticles are considered as very good candidates for smart drilling fluid formulation, i.e., fluids with tailor-made rheological and filtration properties. However, due to the great risk of adapting new technologies, their application in oil and gas industry is not, to date, fully implemented. Over the last few years, several researchers have examined the use of various nanoparticles, from commercial to custom made particles, to formulate drilling fluids with enhanced properties that can withstand extreme downhole environments, particularly at high pressure and high temperature (HP/HT) conditions. This article summarizes the recent progress made on the use of nanoparticles as additives in drilling fluids in order to give such fluids optimal rheological and filtration characteristics, increase shale stability and achieve wellbore strengthening. Type, size and shape of nanoparticles, volumetric concentration, addition of different surfactants and application of an external magnetic field are factors that are critically evaluated and are discussed in this article. The results obtained from various studies show that nanoparticles have a great potential to be used as drilling fluid additives in order to overcome stern drilling problems. However, there are still challenges that should be addressed in order to take full advantage of the capabilities of such particles. Finally the paper identifies and discusses opportunities for future research.

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Nano-Based Drilling Fluids: A Review

With the increased attention toward nanotechnology and their innovative use for different industries including but not limited to food, biomedical, electronics, materials, etc, the application of nanotechnology or nanoparticles in the oil and gas industry is a subject undergoing intense study by major oil companies, which is reflected through the huge amount of funds invested on the research and development, with respect to the nanotechnology. Nanotechnology has been recently investigated extensively for different applications in the oil and gas industry such as drilling fluids and enhanced oil recovery in addition to other applications including cementing and well stimulation. In this paper, comprehensive literature was conducted to review the different applications of nanotechnology in the oil and gas industry. A summary of all nanoparticles used along with a detailed analysis of their performance in improving the targeted parameters is comprehensively presented. The main objective of this review was to provide a comprehensive summary of the different successful applications of nanotechnology and its associated challenges, which could be very helpful for future researches and applications.

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A comprehensive review of nanoparticles applications in the oil and gas industry

Application of In-House Prepared Nanoparticles as Filtration Control Additive to Reduce Formation Damage

Updated criterion to select particle size distribution of lost circulation materials for an effective fracture sealing

Drilling fluid losses are considered one of the major contributors to drilling non-productive time (NPT). Lost circulation materials (LCM’s) have been widely used to avoid or stop losses. Due to the large number of current available LCM’s and their different applications, classification and testing of LCM’s is very important. Conventional LCM’s are currently classified into different categories based on their appearance as fibrous, flaky, and granular or a blend of all three. The most recent LCM classification was published around 50 years ago and this paper intends to fill this gap with an updated classification including conventional and new technologies. We propose to re-classify LCM’s into 7 categories based on their appearance and application as: granular, flaky, fibrous, LCM’s mixture, acid/water soluble, high fluid loss squeeze, swellable/hydratable combinations, and nanoparticles. Particle plugging apparatus (PPA) and HPHT fluid loss apparatus in conjunction with slotted/tapered discs are used to evaluate LCM performance for corrective treatments. Until now, no single standardized testing method or interpretation that evaluates LCM’s performance when preventive treatments are applied in order to increase the fracture gradient has been developed. The difficulty in standardizing the testing methods is due to the disagreement about wellbore strengthening mechanism. This paper discusses the most recent developments in lost circulation materials such as plugging assurance technology and nano-technology, in addition to the presentation of a comprehensive summary of today’s available LCM’s.

Review of Lost Circulation Materials and Treatments with an Updated Classification


 Oil/gas exploration, drilling, production, and reservoir management are challenging these days since most oil and gas conventional sources are already discovered and have been producing for many years. That is why petroleum engineers are trying to use advanced tools such as artificial neural networks (ANNs) to help to make the decision to reduce non-productive time and cost.
 A good number of papers about the applications of ANNs in the petroleum literature were reviewed and summarized in tables. The applications were classified into four groups; applications of ANNs in explorations, drilling, production, and reservoir engineering. A good number of applications in the literature of petroleum engineering were tabulated. Also, a formalized methodology to apply the ANNs for any petroleum application was presented and accomplished by a flowchart that can serve as a practical reference to apply the ANNs for any petroleum application. The method was broken down into steps that can be followed easily. The availability of huge data sets in the petroleum industry gives the opportunity to use these data to make better decisions and predict future outcomes. This paper will provide a review of applications of ANNs in petroleum engineering as well as a clear methodology on how to apply the ANNs for any petroleum application.

Mortadha Alsaba

Papers

A comprehensive review of nanoparticles applications in the oil and gas industry

Application of In-House Prepared Nanoparticles as Filtration Control Additive to Reduce Formation Damage

Updated criterion to select particle size distribution of lost circulation materials for an effective fracture sealing

Review of Lost Circulation Materials and Treatments with an Updated Classification

Applications of Artificial Neural Networks in the Petroleum Industry: A Review