The success of field management depends on the accuracy and availability of well performance data. Continuous monitoring provides information so that corrective action can be taken in a timely manner to better manage expensive well assets by maintaining well potential, managing water conformance and increasing the well life. Accurate water-cut monitoring can significantly reduce the dead well number by providing the data to implement timely corrective action.Methods for measuring water-cut values range from conventional hand sampling to cutting edge technology. Saudi Aramco's traditional well testing practices, utilizing a test trap at a GOSP, limit the information available due to the infrequent tests for an individual well, usually exceeding one month or more. Test trap data also has inherent error built in, due to averaging and human error. What is needed is real-time, in-line and accurate water-cut monitoring.When considering technologies for monitoring watercut, factors such as accuracy, data transfer rate, and cost play major roles. This paper presents how an infrared meter provides an accurate and cost effective means to monitor water-cut in complex wells. The infrared monitoring device is an in-line real-time monitoring system that provides accurate water-cut even, in very challenging flow conditions. A pilot test of the infrared water-cut meter was successfully conducted in a major oil field in Saudi Arabia. Results from this test will be included in the paper.

The Peer Review (PR) concept is a widely practiced process used in various organizations all around the world, and though it is not new, it is very necessary. The Saudi Aramco - Southern Area Producing Engineering Department has taken the initiative to adopt and apply this unique concept to its organizations for more than a year. The PR process has demonstrated to improve production and cost savings/avoidance, to ensure safety issues being in compliance and most importantly, to share with and pass on knowledge among the technical workforce. The intent of this paper is to share our experience with respect to the PR process within the Production Engineering organization. This paper presents the PR processes, including its history, rationale, definition, purpose, scope, benefits, guidelines (including member's qualifications and how the PR session is conducted), flow process, structure, PR qualities and characteristics, tracking system, selection of PR projects and a number of actual case examples accomplished by the PR groups. Introduction The first question one should ask when the subject of PR comes up: What is Peer Review? Before answering that question from a professional perspective, let's view the following cartoons as shown in Figures 1, 2 and 3, in which they implicate in three separate situations and then ask ourselves a question: could these possibly represent the PR practice? The 1st picture1, shown in Figure 1, portrays a situation where the work of a scientist (person on the left) is being critically examined by his peer (person on the right). His work was found to be full of errors, unacceptable and was told to go back and re-do it. The 2nd picture1, shown in Figure 2, depicts a situation where engineer works on a project without consulting with others prior to submitting it to his supervisor for approval. The 3rd picture1, shown in Figure 3, illustrates the level of importance the peer review group (PRG) given. These situations could occur in any actual work environment, and our recommendation is to avoid all of these situations because they do NOT represent the true meaning of the PR Process. In this paper, we describe a PR process that has proven to add value, enhance operations, build collaborative teamwork spirit and has been routinely practiced in Production Engineering (PE). History and Present Day As many of us know, the PR Concept is not a new concept and, historically, we find that it has existed long before our time. We found that the 1st document of the PR process is actually dated back to the year 854–931 European Calendar in a book called Ethics of the Physician by Ishap bin Ali Al Rahwi of Al Raha, Syria about the role of the physicians. In short, the council members (or peer reviewers) had to review all of the physician's notes about his patient's visits to arbitrate whether or not he had duly performed according to the medical standards the cure or death of a patient. Legal malpractice lawsuits could be filed against him if the council members found he did not follow the standard medical practices. Today, the PR processes are being widely practiced in various institutions across the globe on issues dealing with policies and standards. Such places are in academia, business organizations, the government, and, last but not least, the Professional Engineers' Societies (for instance, in our SPE society)

The fourth industrial revolution (IR 4.0) has brought about many exciting and game changing technological advancements in recent years that span across different industries. Our petroleum industry was no exception. In this paper, we will present realizations of IR 4.0's fruitful impact on multiple upstream production engineering and operation problems. The first IR 4.0 technology uses machine learning techniques to predict scale inhibition and design inhibition programs that arrest scale formation. Scale formation is a common oilfield problem that consumes a lot of expense from operators. The machine learning method has shown its ability to curtail such expenses and manage risks associated with scale formation. The second technology is modeling the reliability of downhole Inflow Control Valves (ICVs) and predicting their failure. The technology is based on advanced big data analytics and uses automated statistical techniques to achieve the method objectives. This technology provides production engineers with an analytical decision-making model to predict ICVs failures and suggest the optimum frequency for stroking or cycling of the downhole valves as a preventive maintenance practice. The third IR 4.0 technology is the automated well integrity risk ranking. This particular technology uses smart interfaces and advanced computation algorithms applied on big data to assign (or weigh) risks of a well in terms of well integrity. This intelligent integrity ranking or classification shifts focus to wells prone to integrity failures more than the healthy ones. In addition, the method helps optimize integrity surveillance resources and prevents the obvious setbacks from a well integrity issue. The paper will explain detailed methodologies of all three IR 4.0 technologies and outline expected results from field implementation of those technologies.