AWS for Industries

Empowering collaboration with the OSDU Data Platform for reservoir modeling

Background

To deliver projects on time, global project teams of geoscientists, geomodellers, and reservoir engineers are working much faster than ever before, quite often asynchronously. However, these teams struggle to find, share, and access relevant seismic, well, and interpretation data currently held in data silos, and across disparate systems. Geoscientists need a better, data-centric way of collaborating to meet these demands.

The Open Group OSDU® Forum’s Reservoir Domain Data Management Service (RDDMS), AspenTech contribution to the OSDU Data Platform, recently introduced new domain functionality for reservoir modelling. The RDDMS plays a pivotal role in enhancing collaboration within reservoir modeling and related workflows. It aims to facilitate data sharing, collaboration, and knowledge management within the oil and gas industry, ultimately leading to better decision-making, operational efficiency, and sustainability in reservoir management practices. It provides a standardized data model and guidelines for organizing and managing reservoir data in the oil and gas industry. By providing a centralized and standardized platform for managing reservoir-related data, OSDU Data Platform’s RDDMS makes sure of streamlined access to reservoir data and promotes cross-disciplinary teamwork. This allows geoscientists, engineers, and data analysts to work cohesively on exploration and production projects. RDDMS not only enhances collaboration but also handles fine grained data security and access controls. The standardized data format eliminates silos and enables near real-time data exchange. It allows for seamless integration among different applications and fosters a more efficient decision-making process. The RDDMS significantly improves collaboration by creating a unified and accessible environment for reservoir-related data across the energy industry.

OSDU Data Platform and Energy Data Insights

The OSDU Data Platform is an open-source, cloud-native data platform developed by the Open Group OSDU Forum, which is a cross-industry alliance aimed at the adoption of data solutions in the energy sector. Energy Data Insights (EDI) on AWS is a fully managed service provided by Amazon Web Services (AWS) that enables oil and gas companies to securely ingest, store, and analyze data from the OSDU Data Platform. It is designed to work seamlessly with the OSDU Data Platform, and comes with several essential differentiators, such as Energy Data Insights – IQ (EDI IQ). EDI IQ provides smart data pipelines for at-scale ingestion of your entire subsurface data estate using automated data mapping from source to OSDU with powerful large language models (LLM) and machine learning (ML).

Together, EDI and RDDMS facilitate seamless integration, interoperability, and accessibility of reservoir data across different software applications, disciplines, and organizations, promoting collaboration, efficiency, and informed decision-making in the oil and gas industry.

Enabling collaboration for reservoir modeling

In today’s energy space, collaboration across various disciplines is key to generating accurate reservoir models and driving innovation. To demonstrate the added value of the RDDMS, various reservoir modeling use cases with associated challenges are considered:

1. Multi-discipline collaboration – Various experts such as Seismic Interpreters, Modelers, and Engineers collaborate on the same data, producing and storing different data types within the RDDMS at the different steps of the reservoir modeling process. All combined they generate the reservoir model(s) to support decisions.

2. Challenges in multi-vendor ecosystem – The different SMEs often work in different solutions, provided by different vendors, generating interoperability issues such as data format compatibility, loss of data, or information. RDDMS resolves these issues, making sure of data interoperability throughout collaborative projects.

3. Cross-BU collaboration – Business units (BUs) need to collaborate with other teams such as headquarters or partners to access and refine reservoir models. Role-based permissions in RDDMS regulate access, making sure of efficient collaboration across teams without data duplication.

4. Data query and retrieval – Once the reservoir model is completed and stored, SMEs need to query the data, potentially reuse, or QC some of them. Completed reservoir models in RDDMS enable stakeholders to efficiently query, retrieve, and use data for QC, new studies, and continuous improvement initiatives.

Implementing collaboration through OSDU Data Platform RDDMS

RDDMS organizes collaborative efforts into Dataspaces, acting as project spaces where users can seamlessly contribute, review, and analyze data. For example:

  • User 1 interprets horizons, faults, and well markers stored in the Dataspace.
  • User 2 consumes these interpretations and produces a set of comprehensive surfaces to delineate the main element of the reservoir model and stores it back into the Dataspace.
  • User 3 uses data generated by User 1 and User 2 to build a 3D geocellular model with a set of petrophysical properties, derived from well logs.
  • User 4 conducts a reservoir simulations review based on the model generated by User 3.

The preceding scenario is illustrated in the following figure.

Fig. 1 Enabling collaboration with RDDMSFig. 1 Enabling collaboration with RDDMS

Fine-tuned collaboration with role-based permissions

Permissions within RDDMS are granular and can be defined at the Dataspace level. Depending on their role (such as headquarter, business unit, partner), users can have owner or viewer access to specific Dataspaces. At the Dataspace level, we can define permission by user groups. Based on which user group you belong to, you might have owner or viewer access to RDDMS Dataspace, enabling you to consume data only, or to ingest and consume data. This means that collaboration can be fine-tuned based on your role in the project (headquarters as opposed to business unit, partners, etc.).

Technical design and architecture

Using EDI, geoscientists or engineers can search and get some insights about the data. To make sure that happens successfully, data managers can build manifest for the Dataspace, and ingest into the OSDU Data Platform. Using manifest helps establish the co-relation of the data with RDDMS. EDI users with appropriate permissions can ingest the manifest data for the Dataspace.

Now data search can be performed using the EDI search tool, which calls OSDU search services. The technical design of the overall workflow is shown in the following figure.

Fig. 2 RDDMS workflowFig. 2 RDDMS workflow

Benefits and Conclusion

The benefits of using RDDMS in the OSDU Data Platform are as follows:

  • Cross domain data sharing, interoperability based on RDDMS Dataspaces, using domain APIs.
  • Efficient collaboration using data openness and standard (RESQML) for reservoir modeling workflows in a cross-vendor ecosystem.
  • Accurate data permissions streamlining parallel processes by different teams.
  • Centralized OSDU data discovery for geomodellers through a dedicated portal.
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Yuriy Gubanov

Yuriy Gubanov

Yuriy Gubanov is a Senior Partner Solutions Architect at Amazon Web Services specializing on Energy Data Platforms, including OSDU Data Platform. Yuriy has worked in the energy industry for nearly two decades architecting, implementing and delivering innovative IT solutions for the engineering, geoscience and data management communities. He is an avid cloud computing enthusiast and is always looking for new ways to design and influence the energy systems of the future.

Alice Chanvin

Alice Chanvin

Alice Chanvin is Director, Product Manager at AspenTech, Subsurface Science and Engineering. Before taking this role a decade ago, Alice specialized for more than 10 years in Reservoir modeling in various roles where she met and worked with many operators around the world. During this time, she gained expertise in various G&G contexts and faced the challenges of data silos and data transfer complexity for Integrated Reservoir studies. Her current role is aiming at tackling those challenges, focusing on data management, by integrating and storing modeling and reservoir data in a standard-based open relational cloud database. As part of her current role, she is actively promoting standards in the industry actively participating in OSDU initiative. Alice holds a Master’s degree in Petroleum Geology from Ecole National Superieure de Geologie in Nancy, France. She is currently based in Paris, France.

Christine Rhodes

Christine Rhodes

Christine Rhodes is a Senior Partner Development Specialist for Energy Data Platforms, OSDU. Christine has 16 years' experience in the energy industry working in Petrotechnical Data Management and Project/Program Management, and currently spends her days at AWS tackling industry challenges by diving deep and bringing forward innovative solutions from our growing ISV community. She is passionate about change management and how data and relationships can support the energy transition across the industry.

Priya Choudhari

Priya Choudhari

Priya Choudhari is a principal solution architect at 47Lining, Hitachi Digital Services, with nearly two decades of experience in architecting digital solutions for the oil and gas, healthcare, and aerospace industries. Priya specializes in the OSDU Data Platform and has supported multiple customers in application integration. Prior to joining 47Lining, Priya was a technical lead at Baker Hughes, a GE company, with a focus on delivering software-as-a-service applications for asset performance management. She is deeply passionate about technology innovation.