While all other industries are aligned with the digital evolution, oil and gas operations have also taken advantage of the importance of the digital transformation, especially in the actual context. Our industry is arguably in a new wave of the digital oilfield, with a growing consensus toward "smart" operations and "predictive" maintenance instead of the "reacting better" approach, which is not adequate in the new industry conditions and has been proven as an inefficient approach. Oil and gas operators and services companies have a major opportunity to increase efficiency and reduce operational costs through better asset tracking and predictive maintenance, combined with operations and technology expertise. This paper will focus on the maintenance management of downhole equipment, evolving in an unforgiving downhole environment, which in the case of equipment failure, can cause high financial losses. It will also present a use case and opportunities and challenges of smart monitoring and the predictive equipment maintenance approach, which is supported by newer technologies, such as the industrial internet of things (IIoT) and data analytics that use machine learning (ML) algorithms compared to the traditional, reactive approaches to equipment maintenance.
Depth correlation before perforation is crucial in reservoir testing, to minimize the uncertainties about the reservoir being tested. Currently, three main methods are used to correlate to depth: simple pipe tally, tag of a known element in the well, or a wireline gamma ray (GR) log—which is the most accepted method, owing to its precision and track record. Wireline GR correlation, however, requires additional time (6 to 8 hours), translating into cost for the operator. We describe a new depth correlation tool, which is mounted directly in the drillstem test (DST) string and is enabled by a downhole wireless acoustic telemetry system, that provides correlation algorithm in real time without the need for extra wireline intervention. The introduction of a wireless-enabled GR measurement into the DST string radically changes the workflow for DST operations and results in significant reduction of rig time, as shown by one of our latest job campaigns in Qatar.
Dynamic reservoir data are a key driver for operators to meet the forecasted production investments of their fields. However, many challenges during well testing, such as reduced exploration and capex budgets, complex geologic structures, and inclement weather conditions that reduce the well testing time window can prevent them from gathering critical reservoir characterization data needed to make more informed field development planning decisions. To overcome these challenges, a live, downhole reservoir testing platform enabled the most representative reservoir information in real time and connected more zones of interest in a single run for appraisal wells in the Sea of Okhotsk, Russia. This paper describes the test requirements, the prejob planning, and automated execution of wirelessly enabled operations that led to the successful completion of the well test campaign in very hostile conditions, a remote area, and restricted period. The use of a telemetry system to well testing in seven zones enabled real-time control of critical downhole equipment and acquired data at surface, which in turn was transmitted to the operator's office in town in real time. Various operation examples will be discussed to demonstrate how automated data acquisition and downhole operations control has been used to optimize operations by both the service company and the operator.
Well test is one of the crucial steps required to forecast production investments of their fields. However, the operators face many challenges such as reduced capex, exploration budgets, and bad weather conditions that limit the well testing time window. To overcome these challenges, an automated well testing platform enabled a real time monitoring and controlling more zones in a single run for appraisal wells in the Sea of Okhotsk, Russia. This article highlights the test objectives, the job planning, and automated execution of wirelessly enabled operations in very hostile conditions and limited time period. The use of a telemetry system to well test seven zones allowed real-time data acquisition, control of critical downhole equipment, data transmission to the operator's office in town. Various operational cases will be discussed to demonstrate how automated data acquisition and downhole operations control has optimized operations for both the service company and the operator.
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