The communication of data between various operator and service company data stores has long been problematic. Fragile, low bandwidth lines of communication coupled with a lack of standards have left serious efficiency gaps in the movement of data from the acquisition location to decision-making and interpretation centers. Various systems have been developed and deployed to minimize these difficulties; however, all have fallen short of industry requirements. Recent availability of more robust, higher bandwidth lines between locations has led to a new standard of communication called Wellsite Information Transfer Standard Markup Language (WITSML). Using this new technology, data can be acquired and transmitted synchronously or asynchronously among multiple stakeholders with limited effort. The ability to mix and match various data collection vendors and connect these data sources to interpreters and modelers with limited effort is creating new opportunities to improve the success and efficiency of remote operations. This paper reviews four cases that demonstrate the use of WITSML to synchronously transmit real-time data from domestic and international offshore locations to onshore sites. The cases clearly demonstrate that WITSML meets previously neglected industry requirements of durability, flexibility, economy and ease of use in omni-directional data transmission between rig and shore. Introduction The petroleum industry thrives on its ability to acquire, manipulate and share ever-improving types of data. Numerous industry standards have been developed to ease the transfer and manipulation of this data; however, each is limited by the knowledge and technology available at the time the standard was created. Furthermore, the value of using data synchronously with its acquisition is becoming increasingly more evident. Technology advancements in offshore telecommunications have seen the radio replaced by the facsimile, the facsimile by email and now email by synchronous broadband connections over the Internet. Similarly, decision makers want to replace their static reports with secure, synchronous, dynamic information flowing from multiple vendors to multiple assets and stakeholders. Operators have been historically dissatisfied with proprietary data acquisition and transmission solutions that obligate them to a single vendor because a successful operation typically requires components from multiple data-acquisition companies. These demands were the impetus for the American Petroleum Institute to create the wellsite information transfer specification (WITS) standard for moving drilling data between rig and office-based computer systems. The goal was to standardize rig-to-shore data transmission so that various acquisition companies could communicate with each other and the operator in a common language. Like the standards before it, WITS had numerous limitations that prevented it from becoming a perfectly acceptable solution to the aforementioned demands. WITSML is a collaborative effort to update the widely used WITS. Internet standards-driven and hardware and software platform-independent, this new specification for secure, synchronous and asynchronous data transmission has recently emerged from the testing stage into commercial field deployment. Basic WITSML Design WITSML is a standard for sending wellsite information in a standard format between business partners using Internet-compliant rules (i.e. the familiar XML document format and HTTP/S-based delivery protocols). The content of an XML document is defined by XML schemas. A WITSML data object is a logical organization and grouping of the data items associated with the major components and operations involved in drilling a well. For example, the group known as the rig "data object" contains the data item related to the rig such as its owner, type and manufacture.

There have been significant developments in the evolution of well data aggregation, storage and analytics over the past two decades. Initially, trends were captured on chart recorders and paper charts in the mud logging units, where decisions were based on the experience of the personnel at the rigsite. In general, rig operations were usually successfully completed with the technology available at the time. However, with economic downturns, increased competition, and variations in oil and gas prices, the upstream industry has become far more cost and efficiency sensitive, requiring increased focus on non-productive time (NPT), whether it is due to failures or inefficiencies in the daily operation -we refer to this as Performance Opportunity Time (POT).Through the definition of operational key performance indicators (KPI) and the introduction of intelligent software to calculate and benchmark these KPIs, POT or "flat time" on the drilling curve has been significantly reduced by critically analyzing certain work tasks at the rigsite, combined with remote services. The ability to compare the operational time breakdown for the same type of operation in near real-time across multiple rigs provides the operator with significant insight on the level of operational efficiency at each rig. In combination with remote advisory services, this provides a powerful solution to improve on operational performance This paper illustrates how operational KPI data have been analyzed and benchmarked to enable active focus on recorded POT and the subsequent positive results.

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The prevention of well control incidents requires stringent well-design and casing standards, blowout prevention equipment, safe drilling practices, and multiple layers of controls and workflows. However, industry statistics suggest that most well control incidents occur due to human factors such as misinterpretation of data, delayed response to abnormal well conditions, and drilling crew physical fatigue. Real-time data has long been used by major operators for drilling optimization and well placement activities, but not so much for well control. Exception-based monitoring of real-time data by remote operators can increase operational awareness of drilling crews, who can significantly minimize well control risks by taking proactive and precise actions. However, there are several challenges in the way that current technology is used. Real-time streaming data from a well can consist of 50 to 500 tags that make it challenging to simultaneously and continuously monitor such a large amount of data. The current technology requires determining the well condition from single-curve plots and generic alerts—a technique that is time consuming and allows for errors. Poor-quality data can also adversely affect interpretation, analysis, and decision making. We have developed a new real-time alarm solution to overcome some of the above challenges by combining signal processing and complex logic to manipulate raw and fragmented data and to emulate the thought process of a drilling operator. This real-time system enables drilling operators to set up different alarm thresholds for various activities of well construction such as drilling, tripping, and circulation. A user-friendly alarm console provides valuable situational awareness, enabling the operator to proactively respond to abnormal conditions using real-time alerts based on well condition. The Drilling and Completions Decision Support Center (D&C DSC) team at Chevron Energy Technology Company uses this technology for well control in its global operations. The following paper explains the technology platform of this system, data processing techniques, and some of the drilling events previously identified.

Oil and gas operators use data collected from well operations for real-time monitoring, performance analysis and remote operations. Service providers typically operate real-time data systems from local data centers. They manually provision capex-heavy IT infrastructure and applications for each operator and rig. This may lead to overcapacity and inconsistent performance operating at scale. We commissioned a public-cloud, real-time-as-a-service solution which increased performance and consistency of real-time data access for a Norwegian operator. It also improved the service provider's operating efficiency and ability to accelerate the pace of innovation. A distributed architecture reduces failure points and enables horizontal scaling. Cloud provides elastic scaling to provision the right amount of compute resources to meet demand. Open-source technologies lower maintenance cost and reduce the technical debt accumulated maintaining the proprietary incumbent system. Close collaboration between the operator and service company enabled successful commissioning on six rigs. Real-time data feeds were previously collected by six independent IT systems hosted in a regional data center. The live data streams were successfully transitioned during active drilling activities, without interruption to remote operations. Real-time performance increased by more than 83%. The operator also observed a significant improvement in service and data quality. During the transition period, minor updates were deployed with zero downtime and no impact to the operator. Shortly after rollout, the support team remediated a performance bottleneck in just minutes. Prior solutions would typically require procurement and configuration of network hardware, taking months. In contrast to proprietary software solutions, an open architecture facilitates easy integration of existing software investments. Application programming interfaces simplify the development and connectivity of new real-time applications. Finally, cloud-native solutions accelerate the pace of innovation. Access to cloud services like analytics platforms enable continual integration of digital capabilities with real-time data.