Interoperability of Real-Time Drilling Signals at the Rig Site: An Example Based on Mechanical Specific Energy
Abstract: Digitalization of the drilling process has the potential to improve drilling data quality and consistency, providing support for drilling optimization, safety and efficiency. A significant barrier to realizing this potential is the data streams from the multitude of service companies, which changes almost daily, with variable definition of each of the real-time signals. This paper provides a solution to this problem: a method describing the semantics of real-time drilling signals in a computer readable format.… Show more
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Cited by 6 publications
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Summary Due to the nature of drilling operations, there are several companies collecting data at the rig. The data acquisition system of each company applies its own timestamp to the data. Subsequent aggregation of data (for example, in a data repository) relies on synchronized timestamps applied to the different data sources to correctly collate the data. Unfortunately, synchronized timestamping is rarely achieved. In this paper, we document the different sources of errors in timestamping of data and provide guidelines to help mitigate some of these causes. There are many reasons for the unsynchronized timestamping of data from different sources. It can be as simple as clock synchronization at the rig; each data-providing or -producing company has an independent clock. It can also be due to where the timestamp is applied, for example, at the data source or on data reception. Additionally, it can be due to how the timestamp is applied—at the start of the sampling interval, the midpoint, or the end. Some of the communication methods used at the wellsite, such as mud pulse telemetry that is used to transmit downhole measurements to the surface, have a high, nonstationary latency and the actual acquisition time may vary significantly from the received time. Not correcting the reception time for the transmission delay can result in erroneous timestamping of downhole-acquired data. Timestamping of derived data (data computed from two or more sources) is problematic if the data sources are unsynchronized. Synchronization of clocks within the data acquisition network is therefore extremely important. The resolution of time synchronization depends on purpose; motion control of the rig equipment (for example, the hoist) demands high-resolution timekeeping. However, for the purposes of timestamping acquired data, synchronization to a network time server (a computer with access to a reference clock that distributes the time of day to its client computers over a network) with a resolution of 1 millisecond is sufficient. The issue is agreeing on the common source of time (the reference clock) and agreeing on the passage of time signals through network firewalls. Timestamping is a more involved matter, calling for agreement on standards and, if possible, a computer-interpretable description of the time-related information associated with real-time data. In this paper, we describe in some detail sender vs. receiver timestamping, the downhole to surface timestamp chain, and timestamping of derived data. Systems automation and interoperability at the rigsite—allowing plug-and-play access to equipment and applications—rely on an agreed-upon network synchronization scheme and timestamping methods and standards. Indeed, designing applications that must handle uncertain time adds considerable complexity and cost, not to mention the impact on accuracy and reliability. We present an ordered approach (or guidelines) to a quite resolvable problem. In the last section of the paper, we use a semantic network approach (a semantic graph) to describe relationships for clock synchronization and timestamping (the guidelines and recommendations developed in this paper). A complete description of the semantic vocabulary is provided in an appendix. This makes these guidelines and recommendations digital—able to be interpreted by digital devices—and therefore implementable and auditable.
Summary Due to the nature of drilling operations, there are several companies collecting data at the rig. The data acquisition system of each company applies its own timestamp to the data. Subsequent aggregation of data (for example, in a data repository) relies on synchronized timestamps applied to the different data sources to correctly collate the data. Unfortunately, synchronized timestamping is rarely achieved. In this paper, we document the different sources of errors in timestamping of data and provide guidelines to help mitigate some of these causes. There are many reasons for the unsynchronized timestamping of data from different sources. It can be as simple as clock synchronization at the rig; each data-providing or -producing company has an independent clock. It can also be due to where the timestamp is applied, for example, at the data source or on data reception. Additionally, it can be due to how the timestamp is applied—at the start of the sampling interval, the midpoint, or the end. Some of the communication methods used at the wellsite, such as mud pulse telemetry that is used to transmit downhole measurements to the surface, have a high, nonstationary latency and the actual acquisition time may vary significantly from the received time. Not correcting the reception time for the transmission delay can result in erroneous timestamping of downhole-acquired data. Timestamping of derived data (data computed from two or more sources) is problematic if the data sources are unsynchronized. Synchronization of clocks within the data acquisition network is therefore extremely important. The resolution of time synchronization depends on purpose; motion control of the rig equipment (for example, the hoist) demands high-resolution timekeeping. However, for the purposes of timestamping acquired data, synchronization to a network time server (a computer with access to a reference clock that distributes the time of day to its client computers over a network) with a resolution of 1 millisecond is sufficient. The issue is agreeing on the common source of time (the reference clock) and agreeing on the passage of time signals through network firewalls. Timestamping is a more involved matter, calling for agreement on standards and, if possible, a computer-interpretable description of the time-related information associated with real-time data. In this paper, we describe in some detail sender vs. receiver timestamping, the downhole to surface timestamp chain, and timestamping of derived data. Systems automation and interoperability at the rigsite—allowing plug-and-play access to equipment and applications—rely on an agreed-upon network synchronization scheme and timestamping methods and standards. Indeed, designing applications that must handle uncertain time adds considerable complexity and cost, not to mention the impact on accuracy and reliability. We present an ordered approach (or guidelines) to a quite resolvable problem. In the last section of the paper, we use a semantic network approach (a semantic graph) to describe relationships for clock synchronization and timestamping (the guidelines and recommendations developed in this paper). A complete description of the semantic vocabulary is provided in an appendix. This makes these guidelines and recommendations digital—able to be interpreted by digital devices—and therefore implementable and auditable.
Objectives/Scope Drilling operations rely on the collaboration of many participants, and the efficiency of this collaboration depends on timely exchange of information. The complexity and variability of this information make it difficult to achieve interoperability between the involved systems. Recent industry efforts aim at facilitating the many aspects of interoperability. A central element is semantic interoperability: the ability to correctly interpret the real-time signals available on the rig. This contribution presents an implementation of semantic interoperability using OPC UA technology. It translates the principles developed through joint industry efforts into actual drilling operations. Methods, Procedures, Process The process used the steps of characterizing the drilling real-time data with semantic graphs, and then developing methods to transfer this characterization to an operational real-time environment. A semantic interoperability API (application programming interface) uses the semantic modelling capabilities of OPC UA. Its objectives are to facilitate the acquisition and identification of real-time signals (for data consumers) and their precise description (by data providers). The different components of the API reflect the diversity of scenarios one can expect to encounter on a rig: from WITS-like data streams with minimal semantics to fully characterized signals. The high-level interface makes use of semantical techniques, such as reasoning, to enable advanced features like validation or graph queries. Results, Observations, Conclusions The implementation phase resulted in a series of open-source solutions that cover all the stages of semantic interoperability. The server part integrates real-time sources and exposes their semantics. Data providers can use dedicated applications to accurately describe their own data, while data consumers have access to both predefined mechanisms and to more advanced programming interfaces to identify and interpret the available signals. To facilitate the adoption of this technology, test applications are available that allow interested users to experiment and validate their own interfaces against realistic drilling data. Finally, demonstrations involving several participants took place. The paper discusses both the testing procedures, the results and insights gained. Novel/Additive Information The solutions described in this contribution build on newly developed interoperability strategies: they make on-going industry efforts available to the community via modern technologies, such as OPC UA, semantic modelling, or reasoning. Our hope is that the adoption of the developed technology should greatly facilitate the deployment of next generation drilling automation systems.
Drilling Systems Automation: Fault Detection, Isolation and Recovery Functions for Situational Awareness
Drilling process automation solutions provide positive assistance to the driller, and increase consistency in execution of drilling procedures. However, in drilling automation the use of automated drilling advisors can reduce human operator situational awareness. Therefore, systems that automatically detect and react to drilling incidents must support the driller. These critical systems cover Fault Detection, Isolation and Recovery (FDIR) functions. This paper presents a method that facilitates the interoperability of drilling automation advisors for FDIR functions. Some drilling events happen so fast that mitigation (FDIR) must be implemented directly at the automated drilling control system (ADCS) level. Yet, FDIR functions often need dynamic parametrization from external sources since the ADCS may lack access to mandatory information needed for correct detection and mitigation of the incident. This requires interoperability, communications without human intervention, between the ADCS and the external sources of the parameters for the FDIR function. To interconnect the two sides of the problem, the ADCS describes its capabilities for fault detection and isolation and the external application, the automation Advisor, adapts to the exposed capabilities. On the one hand, the ADCS may implement various types of FDIR functions. On the other hand, external dynamic parameter functions may only address certain types of drilling incidents. Different ADCS providers implement such FDIR functionalities in different ways. Since this undermines the portability (interoperability) of the solutions provided by third party advisor applications, any drilling systems automation solution must address this communication issue. The simplest form of communication describes predefined capabilities, providing the ability to communicate based on an agreement about a set of statically defined possibilities. At an intermediate level of complexity, the ADCS describes its capabilities in a descriptive format that the external application interprets, and to which it can adapt. In the most advanced version, the ADCS describes that it allows the external parameter provider to configure the ADCS behavior to its needs. The paper describes a generic data model covering all three levels of the interface. Another implementation of the model is in the form of a micro-service that implements a REST API and exchanges Json formatted data objects. The latter is therefore agnostic to programming languages and computer platforms. This work is part of the D-WIS (Drilling and Wells Interoperability Standard) initiative advancing industry wells digital systems interoperability. D-WIS is a cross-industry workgroup providing the industry with solutions to facilitate interoperability of digital and computer systems at the rig site. The proposed solution delivers retrofitting ease for existing solutions but is sufficiently flexible to accommodate to new and not yet known FDIR functions. It is a key function for systems interoperability at the rig site, directly addressing situational awareness for the driller.
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