This paper provides an integrated overview of the water shutoff operations, starting from the causes to the solutions. The paper begins with explaining the benefits of eliminating excessive water production. Then, the different types of water production and their properties are explained. The paper also focuses in reviewing the disadvantages of producing unwanted water as well as the sources of it, followed by an explanation of the methodology for identifying the problem. Then, the chemical solutions for water shutoff are reviewed which are generally applied to solve the excessive unwanted water production in the reservoir or near the wellbore area. Finally, the paper illustrates the common mechanical solutions for water shutoff within the wellbore. The aim behind this paper is to provide a general description of identifying the unwanted water production sources and the common practices for water shutoff operations.

Summary Design of drilling fluids, spacers, cement slurries, and fracturing fluids is often done by trial and error in the laboratory. In the first step, the required properties of these fluids are categorized and then efforts will be started with a rough idea of the optimal composition. This first guess usually depends on the experience of the laboratory analyst or fluid engineer. Afterward, the trial-and-error testing starts, and it continues until the fluid design moves closer to the desired fluid criteria. There are several test data that would not be used in this method, and it is difficult to digest a large amount of information by the user. Trial and error could be time-consuming, very costly, and misleading. Today, there is a need for an intelligent system that uses all the available data (big data), even if the data sets are not close to the desired goal, and offers insights for fluid designs. This paper conducted a study on the application of machine-learning-based methodologies, including Gaussian-process regression (GPR) and artificial neural networks (ANNs), to reduce the costs of testing, integrate available experimental data, and eliminate the need for personnel supervision. These practical nonlinear-regression methods empower efficient and fast prediction tools that do not require including complex physics of the underlying system while integrating all available data from different sources. GPR, which is also known as Kriging in geostatistics literature, has exceptional advantages over traditional regression methods because it does not require a known form for regression function and also has the capability of determining the estimation error and the confidence interval. This machine-learning-based tool offers insights for intelligent fluid design and could reduce costs.

We experimentally studied intense femtosecond pulse filamentation and propagation in water for Bessel-Gaussian beams with different numbers of radial modal lobes. The transverse modes of the incident Bessel-Gaussian beam were created from a Gaussian beam of a Ti:sapphire laser system by using computer generated hologram techniques. We found that filament propagation length increased with increasing number of lobes under the conditions of the same peak intensity, pulse duration, and the size of the central peak of the incident beam, suggesting that the radial modal lobes may serve as an energy reservoir for the filaments formed by the central intensity peak.

This study presents a novel approach for bundle of tubes modeling of permeability impairment due to asphaltene-induced formation damage attenuated by ultrasound which has been rarely attended in the available literature. Model uses the changes of asphaltene particle size distribution (APSD) as a function of time due to ultrasound radiation, while considering surface deposition and pore throat plugging mechanisms. The proposed model predicts the experimental data of permeability reduction during coinjection of solvent and asphaltenic oil into core with reasonable agreement. Viscosity variation due to sonication of crude oil is used to determine the fluid mobility applied in the model. The results of modeling indicate that the fluid samples exposed to ultrasound may cause much less asphaltene-induced damage inside the porous medium. Sensitivity analysis of the model parameters showed that there is an optimum time period during which the best stimulation efficiency is observed. The results of this work can be helpful to better understand the role of ultrasound prohibition in dynamic behavior of asphaltene deposition in porous media. Furthermore, the present model could be potentially utilized for modeling of other time-dependent particle induced damages.

To minimize fluid loss and the associated formation damage, underbalanced coiled tubing (CT) is one of the preferred methods to perform cleanout operations and re-establish communication with an open completion interval. Because of their high viscosity and structure, stable foams are suitable cleanout fluid when underbalanced CT operations are applied. However, unstable foams do not possess high viscosity and as a result, they are poor in cleanout operations, especially in inclined wellbores. This study is aimed to investigate the effects of wellbore inclination on the stability of foams. In this study, foam drainage experiments were carried out using a flow loop that has foam drainage measurement section and pipe viscometers. To verify proper foam generation and validate the accuracy of measurements, foam rheology was measured using pipe viscometers. Drainage experiments were performed with aqueous, polymer-based, and oil-based foams in concentric annulus and pipe under pressurized conditions. Tests were also conducted at an inclined orientation to examine the effect of wellbore inclination on the stability of foams. The foam bubble structure was examined and monitored in real-time using a microscopic camera to study bubble coarsening. The foam quality (i.e. gas volume fraction) was varied from 40 to 80%. The drainage rate was slightly higher in the pipe section than in the annulus. More importantly, the drainage rate of foam in an inclined configuration was significantly higher than that observed in a vertical orientation. The inclination exacerbated foam drainage and instability substantially. The mechanisms of foam drainage are different in inclined configuration. In inclined wellbores, drainage occurs not only axially but also laterally. As a result, the drained liquid quickly reaches a wellbore wall before reaching the bottom of the hole. Then, a layer of liquid forms on the low-side of the wellbore. The liquid layer flows downward due to gravity and reaches the bottom of the hole without facing major hydraulic resistance of the foam network. This phenomenon enhances the drainage process considerably. Although foam drainage experiments are reported in published literature, there is limited information on the effects of geometry and inclination on foam drainage and stability. The information provided in this article helps to account for the impact of inclination on foam stability to improve its CT cleanout performance in directional wells.