The recovery of unconventional oil such as heavy oil is receiving great interest as the world oil demand is increasing along with relatively high oil prices. Producing such high viscosity oil is complex and challenging, which usually require thermal techniques. Thermal recovery methods are widely used to recover the heavy oil and bitumen basically by thermally reducing oil viscosity, improving the mobility ratio and enhancing the heavy oil displacement. In response to the recent effort of leveraging heavy oil and tar plays in Saudi Arabia, Saudi Aramco has launched a new thermochemical research program to tackle challenges associated with lowering oil viscosity to improve well productivity and the overall reservoir depletion efficiency. One of the promising new technologies is enabling in-situ steam generation by chemical reaction (EXO-Clean) to mobilize the low API crude oil or tar reserves. In this paper a new steam flooding methodology will be introduced and compared with existing technologies. Steam will be generated in-situ by chemical reactions, which will have better efficiency and lower cost compared to conventional steam injection methods. Simulation study, lab experiments, and field treatment showed great promises of the technology. The developed EXO-Clean treatment relates to in-situ steam generation to maximize heat delivery efficiency of steam into the reservoir and to minimize heat losses due to under and/or over burdens and non-producing areas. The treatment consists of injecting exothermic reaction-components that react downhole and generate in-situ steam and nitrogen gas. The generated in-situ steam and gas can be applied to recover deep heavy oil, and tight oil reservoirs, which cannot be recovered with traditional steam injection methods.

Failures of Electric Submersible Pumps (ESPs) are common occurrences in the oil industry. The random nature of these failures results in production disruption that amounts to hundreds of millions of barrels of lost or deferred oil production annually. Although important improvements have been made in the last fifteen years on ESP sensors, data collection and communications systems, the industry still lacks a system that can provide ESP health condition monitoring with the capability to accurately predict impending ESP failures. The intent of this study was to evaluate the value of Principal Component Analysis (PCA) as a tool to detect developing ESP failures and predict remaining operating time before failure. Complete historical data of five ESP installations was used. For each installation, a stable region was selected to construct a PCA-based model, which was later used to find projections for the whole data set on the principal component axes. Different techniques were used to correlate projected data with the original data and to draw the conclusions of the study. The analysis showed that PCA data scattered away from the origin before the occurrence of each of the failures. But a more powerful observation was that PCA projections showed distinctive data clusters representing subtle changes in the system that are not apparent by directly examining the actual measured parameters. This study concluded that PCA has potential to be used as a tool to identify dynamic changes in the ESP system and therefore to detect developing ESP problems. PCA can also be used as unsupervised Machine Learning (ML) technique to identify hidden patterns and as an essential pre-processing technique for other ML algorithms. PCA can be used as the foundation for the development of better tools for detection of developing ESP failures and prediction remaining ESP run time.

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A maximum reservoir contact (MRC) well, by definition, is a single or a multilateral horizontal well with more than five km of total contact with the reservoir rock. Planning of these wells requires extensive modeling studies to optimize total length, placement and configuration of branches. The main objective behind the MRC well concept was to improve individual well productivity and hence reduce the unit development cost and to better develop hydrocarbon assets. In fact, oil fields developed using MRC wells shows significant improvements in those wells performance in terms of increased PI, lower drawdown, and significantly delaying water and gas conning. A major challenge that faces production engineers in their daily operations is identifying and accessing laterals windows in those MRC multilateral wells, in order to preform rigless downhole sensing and intervention jobs (logging, stimulation, etc.). This challenge varies in difficulty based on the technology advancement of multilaterals (TAML) level, for example in TAML level 2 wells (cased mainbore) metal logging tools such as casing collar locator can be used to identify and confirm the access of laterals, while this of course is not an option in TAML Level 1 multilateral wells (open hole mainbore and lateral). Another reason selective re-entry of TAML Level 1 is considered very difficult is due to the shape and quality of the wellbore near the junction (window), post drilling and after distortion of hydrocarbon flow.  This paper presents an intelligent electromechanical tool, jointly developed to address this issue. The tool consists of a sensing package that can identify and locate the depth and orientation of the lateral window using US and EM sensors, and an electromechanical arm that can be easily rotated and actuated with a wide range of angle, to lead and steer the bottom-hole assembly into the required lateral. This paper also presents the discoveries, challenges, and results of testing this intelligent tool in two TAML Level 1 multilateral oil producers, one fishbone well with a mainbore and six open hole laterals branching from it (shut in conditions) (Mohannad Abdelaziz, 2016), and the other is an open hole well mainbore with a lateral branching from it (shut in, flowing conditions). In Both trials the tool was successfully used to guide a production logging tool into different wells laterals.

The number of MRC (Maximum Reservoir Contact) wells has increased significantly since they were first introduced in 2002. Most of these wells use multilateral well configuration to increase the contact with the reservoir and therefore the well productivity. (Salam Phillip Salamy, 2007) One of the main challenges for multilateral wells is the selective accessibility of the well during the production phase to perform various rig-less activities (such as stimulation, production logging, water shut-off… etc.). This requires detection and confirmation of lateral window depth and orientation and means to allow the tool to be selectively steered into the desired lateral. From all multilateral well configurations classified by TAML (Technology Advancement of Multi-Laterals), Level-1 (openhole mainbore and lateral) is considered the most difficult to re-enter. This is caused by the fact that the shape and quality of the wellbore near the junction is highly unpredictable after the early lateral window construction and the later distortion by the flow of hydrocarbons. Since both the mainbore and laterals are openhole, the simple metal dependent logging tools (such as CCL: casing collar locator) cannot be used as a way to confirm the successful entry of the openhole lateral as in Level-2 TAML (cased mainbore). Well Lateral Intervention Tool has been jointly developed to address this issue. The tool has two main sensory packages (ultrasound and magnetic) to obtain the lateral details (depth and orientation) and an electromechanical arm that can be actuated with different angles to guide the BHA inside the required lateral. This paper presents the challenges and outcomes of the tool field trial in a Level-1 multilateral well. The oil producer candidate has an openhole mainbore and six openhole laterals branching from it (fishbone well). The tool has been successfully used to guide PLT (Production Logging Tool) into three of the six laterals limited only by Coiled Tubing reach.