Metal Oxide Nanoparticles (MONPs) comparison has been used for the first time as Nanoshale inhibitors in water-Based Drilling Fluids. These Nanoshale inhibitors used in this study eliminate the use of toxic high potassium chloride (KCl) concentration in shale drilling operations and environmentally friendly with reducing the cost of drilling fluid treatment and waste disposal. The dispersion test of Nanoshale inhibitors based on MONPs with shale samples revealed to be an effective candidate with significant interaction reduction between the drilling fluids and the shale particles compared without these Nanoshale inhibitors samples. This new Nanoshale inhibitor maintains the integrity of the cuttings and minimize the interaction of fluids with shale sections during the rolling test. Zeta potential (ZP) has been conducted to determine the charge of shale and nanoparticles samples. Although the application of nanoparticles to improve the performance of conventional water-based drilling fluid was studied by researchers, it is the novelty of this research to eliminate use of KCl and to develop the new generation of Nanoshale water-based drilling fluid with economical consideration and lower environmental impact.

While many factors influence the success of a given well, the permeability of the surrounding formation is one of the most important properties to understand the nature of any reservoir and to be utilized for effective oil and gas drilling. Gathering data from well logs for different wells can be highly expensive and time-consuming. The goal of this work is to find the best artificial intelligent model which can predict the permeability values with minimum error while saving time and money. Therefore, accurately estimating is highly beneficial to use such a model for further field and engineering applications. In this project, a trial was accomplished through a Machine Learning (ML) approach using several modules of Artificial Intelligent including ANFIS and ANN to examine and build a permeability prediction model based on nine (9) well-logging parameters taken from well-logging data measured at a borehole in carbonate rock. The permeability was predicted from well-log data using Artificial Intelligent (AI) technique. Field data were recorded at one borehole, where all logs are correlated together. After obtaining results, the prediction model can be considered successful, it is highly recommended to utilize ANFIS- Genfis2 as it gives outstanding results as the correlation coefficient training was 1.0 and testing was 0.9347 compared with ANFIS-Genfis1 which was not satisfying with training correlation coefficient of 1.0 and testing 0.4073, including a significant reduction in the percentage error of 14.3% compared of 301%, and utilize ANN with a double layer not single, as the result of single layer showed a correlation coefficient of 0.9337 in training and 0.9924 in testing. In addition, single layer method showed higher error compared with double layer. Conclusively, it is recommended to apply the model with other data obtained from the same reservoir, to minimize the number of unneeded data, enhance the measurement performance by avoiding human errors, and develop other relationships between a set of parameters that can result in a better and most effective prediction model. In novelty, utilizing and studying the output of this trial application of the machine learning approach will summarize the best models and techniques for predicting many important reservoir properties such as Permeability. The number of well logging parameters is high and has been statically analyzed to increase the resolution of the input data. Building this prediction model will increase the recovered amount from the subsurface and will lead to significant cost savings in drilling and exploration operational

This paper will discuss the largest coiled tubing acid stimulation operation completed on a water injection well in Saudi Arabia. Stimulation design, field execution and the well performance before and after the treatment as well as massive planning, logistics and coordination are the key elements of this discussion. Furthermore, the authors would like to briefly review the future plans for other long/ multilateral wells in the area. This job was conducted on a dual lateral horizontal power water injector. The objective of this job was to stimulate the formation of both laterals by pumping 20% hydrochloric acid (HCL) and 20% strength diesel-emulsified acid and diverting it with 20% viscoelastic surfactant based acid on using Coiled Tubing (CT) and a Multilateral Tool (MLT). A total of 10,335 ft horizontal interval was successfully stimulated with 362,700 gallons of treatment fluid in 27 stages using 2 3/8" CT. On this job the MLT was successful in locating each lateral. The post-acid injection rate has been increased by more than double, higher than initial expectations. Consequently, the injectivity index has been increased drastically above the field average. Based on success of this stimulation job, the concept of designing and treating other Maximum Reservoir Contact (MRC) injectors using this technique becomes a recommended intervention process. The key to enhance future jobs lies on the ability to effectively capture and use the lessons learned from this massive operation. The continuous success of these jobs will help to improve the water injection system in Ghawar field and will enhance oil recovery. Background Saudi Aramco drilling strategy has been rapidly progressing through several sequences in order to optimize the oil production, water injection and cost. Accordingly, a new generation of wells are being widely drilled and completed with multiple legs or laterals in the horizontal section of the desired formation. This type of horizontal well has been implemented in the Ghawar field. Although multilateral wells have proven their efficiency to meet the strategy, the complexity of well intervention becomes a challenge for Operating and Service Companies. Logging, stimulation and other downhole surveys are major and difficult tasks. Currently the situation is better and the well intervention work can be conducted on an individual lateral as a result of utilizing the MLT re-entry tool. It depends on mechanical and pressure differential without an electric line or guidance system. Also, it can be used in conjunction with other CT downhole tools. Case History Well-A is a Power Water Injection (PWI) well which was drilled in 2002 as a dual-lateral horizontal open hole to have a maximum reservoir contact and support oil production in a carbonate reservoir which is a relatively tight formation. The well was drilled with two laterals across Arab-D Zone 2A. The 6 1/8" main bore, lateral 1, was drilled to a Total Depth (TD) of 13,649 ft Measured Depth (MD) and lateral 2 was drilled to a TD of 13,676 ft MD. The 7" liner was set at 7,686 ft while the window depth is at 8,720 ft (see Fig.1 below). Job Justification The objective was to acidize the carbonate formation of both horizontal laterals by pumping plain 20% HCL acid and diesel-emulsified 20% HCL (SXE) acid and diverting it with viscoelastic diverting 20% HCL acid (VDA) using a Coiled Tubing Unit (CTU) and MLT.

Background:Microbial communities that colonize insect guts contribute positively to the absorption of nutrients, immunity and the overall health of the host. Recent studies have been tapered towards only economically important arthropods, particularly honeybees. On the other hand, arthropods such as grasshoppers are considered as pests because they create havoc leading to economic losses. Grasshoppers are considered phytophagous pests that have a large appetite for plant fibers, whose digestion depend largely on the bacterial communities in their guts. This study characterises the gut microbiome in Usherhopper, Poekilocerus bufonius using the metagenomics methods through the next generation sequencing (NGS). Results:A total of 59,072,222 bacterial reads were recorded which were classified into phylum and genus levels. Proteobacteria were the most shared at the phylum-level whereas Wolbachia were the most dominant genera based on the total reads. Conclusions: The host-microbiome interactions and their perceived influence on the ecosystem are yet to be fully explained, therefore a detailed study is pivotal in order to enforce effective conservation and pest management.

Environmentally friendly Mesoporous Silica Nanoparticles (MSNs) has been used for the first time as a Nanoshale inhibitors in water-Based Drilling Fluids. Nanoshale inhibitors used in this study eliminate the use of toxic high potassium chloride (KCl) concentration in shale drilling operations and reduce the waste management associated cost with drilling fluid treatment and disposal. The dispersion test of MCM41 Nanoshale inhibitor with Silurian shale samples revealed to be an effective candidate with significant interaction reduction between the drilling fluids and the shale particles. This new Nanoshale inhibitor maintains the integrity of the cuttings and minimize the interaction of fluids with shale sections during the rolling test. XRD patterns has been conducted to determine the crystalline structure of shale and nanomaterial samples. Although the application of nanomaterials to improve the performance of conventional water-based drilling fluid was studied by researchers, it is the novelty of this research to eliminate use of KCl and to develop the new generation of Nanoshale water-based drilling fluid with economical consideration and lower environmental impact.