Energistics

Abstract The rapid pace of digitalization of E&P operations is generating a sharp increase in the volume of data being exchanged between different disciplines, departments, partners and vendors. To facilitate the exchange of data across these many entities rapidly and in a uniform manner and with no loss of information, the ETP (Energistics Transfer Protocol) WebSocket-based two-way protocol, originally introduced in 2014 and updated in 2016 (McKenzie 2016) to support streaming of real-time data from drilling rigs to onshore monitors, has been expanded. The standard ETP data streaming protocol delivers a near-instant streaming of data from rig to onshore centers with the additional ability to entertain multiple connections to perform the streaming to several recipients concurrently. Modes were also present in that version to make use of the protocol for direct application interoperability. However, the latter were not fully developed and as a result saw limited uptake after the publication of the standard. The new version of the protocol aimed at improving the real-time data streaming capabilities based on the experience accrued over 3 years of deployment, as well as completing the interoperability features and adding new sub-protocols to support the interrogation and selective retrieval of data from a server as well as other actions that facilitate direct application interoperability. A data system or application can be set to signal to listening systems instances of a new object or changes to existing objects. Each interoperability connection is initiated by an application acting as a client and connecting to an application that is an active server at that time. Once the connection is in place, the duplex or bi-directional nature of the protocol stack makes it possible for either application to make requests to the other one. These application interoperability capabilities offer an alternative to the existing data transfer process that uses files as a mechanism to move data from one application to another. The file-based process remains relevant for transmittals that require the creation of a data package that can be loaded into systems not connected to the same network, as well as for archival purposes.

Cost reductions have become an essential response to lower oil and gas prices. Drilling rigs operate in distant and sometimes hostile environments, so relocating rig-based experts to remote control centres saves costs and improves health, safety and environment (HSE). Key staff can work in an improved environment and movements to-and-from the rig are fewer, lowering transport-related costs and risks. The offsite experts can apply their expertise to the operations of multiple drilling rigs from a single location. To make this a reality, data from thousands of sensors on the rig and from measurement devices such as logging while drilling must be fed to the control room instantaneously and continuously. Legacy systems that poll rig-based devices for new data consume significant bandwidth and deliver data in a discontinuous manner with delays of 15 s or more. This does not meet the criteria for safe and reliable remote control of a rig and has been the reason why many roles have remained rig-based. This paper describes a new set of protocols that establish a continuous stream of data from devices on the rig to the control room with sub-second lag time. The new protocol also uses an order of magnitude less bandwidth, thus allowing more data to be carried in less time. Associated with industry-standard well-site information transfer standard mark-up language data transfer formats, the process operates with numerous service providers and software systems transparently. This paper includes a case-study to which the new protocol is applied, resulting in fewer permanent staff on a North Sea rig and fewer visits by an intervention contractor to the rig, with clear cost savings and HSE risk mitigation.

Abstract Objective/Scope Exploration and production (E&P) work flows continue to evolve in completeness and complexity. Multidisciplinary teams use a variety of software packages to perform the many tasks required to build and update accurate and comprehensive earth models used over the life of a field. Continued data-gathering and iterations to characterize the range of uncertainty is an integral yet challenging part of the process. Incorporating new data into an existing model can be "painful"—time consuming, tedious, and error prone—which inhibits our ability to easily and accurately update a model. Methods, Procedures, Process RESQML is the industry-defined data-exchange standard used in E&P to transfer earth models between software applications in a vendor-neutral, open, and explicit format. In Version 2.0.1 (published in September 2015), RESQML defines a richer, more complete set of data objects (than Version 1) across the subsurface work flow. RESQML now also defines precise classifications of data objects and the relationships between them to create a knowledge hierarchy of: abstract subsurface features, human interpretations of those features, the data representations of those interpretations, and the properties indexed onto those representations. These and other new features now make it easier to exchange data, iterate, and update models along the entire subsurface work flow. Result, Observations, Conclusions This paper presents a work flow—using actual data from the Alwyn North Field—for adding "one more fault" to a structural interpretation after a preliminary unsatisfactory history-matching exercise in a flow simulator. The paper describes how the RESQML v2.0.1 data-exchange standard can support a repository for geological knowledge and how multiple RESQML-enabled software packages (structural and stratigraphic interpretation applications and reservoir modeling systems) can share, transfer, and iterate on a coherent model. The work flow is based on a test case used to demonstrate interoperability of multiple software packages from various member-companies (operators and service/software companies) of Energistics, the upstream oil and gas data standards organization. All along the reservoir model cycle, Energistics members exchanged: individual interpretations (e.g., for horizons, faults, wellbore trajectories and formation markers), their individual representations (e.g., scattered points, surfaces, wellbore logs, and blocked wellbores), composite interpretations (e.g., structural, stratigraphic, and reservoir organizations) with their framework and grid-based representations and properties. The paper explains how the members produced a reservoir model, then updated and exchanged only the model elements required to change when a poor history match indicated an important fault was missing from the initial structural interpretation and had to be added to the model. Novel/Additive Information The new RESQML v2.0.1 design and capabilities mean E&P professionals can now transfer complete models with all data in context and/or logically transfer (update) only the parts of a model that have changed. This new v2.0 functionality is a significant improvement over RESMQL v1.1 and its precursor, RESCUE, both of which could only exchange a smaller set of individual elements and none of the relationships between them.

Abstract The current standard infrastructure for delivery of wellsite data uses SOAP Web services over the HTTP protocol. More than a decade of experience in this environment has revealed significant challenges for timely delivery of wellsite data. At the same time, data volumes are increasing exponentially in an ever more connected world. To address these issues, an entirely new protocol stack, based on the latest available Web standards, has been developed. The Energistics Transfer Protocol, or ETP (Energistics 2016), is a new communications protocol specification that enables efficient transfer of data between rig site, office, and applications. The initial use case is for real-time data; however, it is anticipated that ETP will be expanded to include functionality for historical data queries. ETP has been specifically envisioned and designed to meet the unique needs of the upstream oil and gas industry and specially to facilitate the exchange of data in the Energistics family of data standards, which includes WITSML™, PRODML™ and RESQML™. One of the initial goals of ETP is to support everything from WITS-style devices through to html5-enabled mobile devices with a single, simple-to-implement protocol. Some of the main use cases are to move real-time data between applications, including: Device to wellsite provider (acquisition system)Transfer from a wellsite provider to a WITSML store (aggregation server)Transfer of data from WITSML store to WITSML store (server replication)Transfer of data from WITSML store to client applications ETP defines a notification mechanism so data receivers do not have to poll for data and can receive new data as soon as they are available from a data provider. This paper presents the challenges faced by the industry, a description of the alternatives and technology choices that have been made, and an analysis of performance improvements based on laboratory and field trials for both WITSML (drilling) and RESQML (earth modeling/reservoir).

Abstract Big data analytics (BDA) is a maturing technology that is gaining momentum in the upstream oil and gas industry. The practice centers on aggregating all data from different sources into a "data lake" or equivalent storage for analytics and reporting. But if the quality of the data coming into the lake is unknown, uncertain, or poor, the results derived from analytics may not be reliable. To help determine whether the data is fit for purpose, WITSML v2.0 has some significant new capabilities including a new Data Assurance object and improved metadata on the redesigned Log object. Trusted data is the foundation for all analytical and reporting initiatives. The Data Assurance object does not determine the data quality; rather, it provides the means to transmit assurance that business policies and supporting rules are met in the data transfer process. This capability means that users can apply their own data quality processes, algorithms, and transformations to ensure the data are fit for purpose, auditable, and traceable to meet their business objectives. For example, data assurance policies and rules supporting sensor precision and calibration can be transferred between applications that validate the data according to a company's business requirements. The newly designed Log object and addition of key metadata will address some of the historical organizational challenges of previous versions of the WITSML Log object and enable more intelligent data mining and more efficient and automated use of larger datasets. For example, the WITSML v2.0 Log object references classes of the Practical Well Log Standard (PWLS), an industry standard that lists and defines service company mnemonics. This capability supports a use case such as "give me all the sonic logs" regardless of vendor. As a side activity, but driven by the needs of WITSML users, the PWLS is also being updated. The combination of these capabilities can help increase users' trust in their data, improve analytics, and ultimately help companies to realize more value from big data analytics and its ability to help upstream oil and gas improve safety, reduce operational risk, and improve efficiency.