Automating Design Workflows in Upstream

The energy industry has always been known for its cutting-edge technology. In today’s world we no longer look to just mechanical tools for innovation but to revolutionary digital technology to bring our industry the next phase of energy exploration.?

OMV Exploration & Production is pursuing a strategy to become a digital frontrunner in the Oil & Gas upstream industry. Three years ago, the senior management invested heavily in preparing for a rapidly changing industry landscape. Key projects that were established at that time are coming to maturation. One involved the automation of workflows for types of capital projects that are common in upstream – the design, planning, and execution of oil & gas wells.

Workflow automation is now a common topic in industry. Most efforts in upstream to date have focused on simple processes or have limited themselves to phases within a process. OMV with its partner Schlumberger has succeeded in the automation of an entire multidiscipline gated management process from concept design to execution. The workflow manages multiple databases and data sets for planning. The execution program is generated automatically, and a built-in feedback loop takes efficiency insights back into the planning cycle. The work here represents a major step forward in the upstream industry.

?OMV Exploration & Production has a very talented technology and information team but is not a software company. The company needed to work closely with a strategic partner on the development of workflow automation. Schlumberger Solutions, one of the main providers of software tools to the upstream industry signed a strategic partnership in 2019 with OMV Exploration & Production and the companies formed an integrated team to work on the project.

Well Delivery is a project management process that requires contribution from multiple disciplines from geology and reservoir engineering, civil construction, chemical engineering, and corrosion engineering among others depending on the location and well type. Each discipline has evolved specialized digital tools to model their respective tasks with the outputs framed to best manage their understanding of the issues. These types of projects are normally managed through a gated process with standard orchestration tools. The typical duration of one of these projects is 18 months for a standard midrange well. OMV’s ambition was to reduce the planning time significantly for the first well in a project to eight months with subsequent wells down to a day.?

The first phase began with a thorough analysis of the workflows and how information is transferred between disciplines. The people involved in the design process are often the brightest engineers and scientists in the company. They are constantly looking for a way to organize and restructure information and data to formats that make the most sense and are most useful to them. OMV discovered that data was being transferred between models in many formats including spreadsheets, slide packs, text and Ascii files. Managing all of this adds significant time, frustration, and a loss of quality of data. It is not unusual to find a wide range of formats and file structures that are not consistent across multiple projects. OMV needed a solution that would address all these concerns.

OMV also looked at the workflow paying particular attention to feedback loops and re-engineering steps. There are lots of feedback loops identified as essential to optimize each model to reach the best possible overall solution. A representative spaghetti diagram is included as Figure 1:

Figure 1: “As Is” Well Design Workflow

?Well Delivery uses scheduling software to manage its critical planning objects. Many companies are moving to orchestration tools which capture the outputs from many flows and allow people to automatically update their progress and gate keepers to review reports and conclusions in an online environment. Without a common database platform sequential logic still is core to an orchestration workflow. Feedback loops are not captured or, if captured, are shown as specific events (e.g. plan the limit exercises). To achieve the step change in performance OMV is looking for a move from sequential activities to simultaneous activities, OMV needs to automate data transfer, orchestration, execution instruction creation and access to history/incident databases.

Orchestration tools can bridge these gaps by having passive (pointing) links, but Automated Workflows need to have dynamic links. A design change or decision needs to be reflected in multiple workfronts. The many workflow engines need to access the same data. Every element has to have a common format and location - a universal database which can be accessed using Application Programming Interfaces (API’s). The end point of the project is a digital integrated environment as visualized as figure 2.

Figure 2 Solution Design

The upstream industry has been working on a common data platform known as the Open Subsurface Data Universe (OSDU). The platform is not complete but it has matured significantly in the last year. The data architecture is at a level that companies can build software tools that can share data between multiple applications.

So why go through all this effort? The benefits for the company need to be identified before committing a major capital, cultural and resource investment. It can be very difficult to quantify what a change in automation can bring. Productivity enhancements are often hard to evaluate initially. Functional organizations typically have project budgets that work on a bulk mode. Individual steps are not costed so the benefit of automation, while being intuitively obvious, are hard to quantify. The main benefits are:

Substitution: The simplest of tasks e.g., compiling data to share, checking the accuracy and currency of data, can consume up to 60% of workforce time. The OSDU discussed above is an excellent example of the substitution benefit of automation by the reduction of data exchange interfaces.

Enhancement: Improved visualization and decision-making tools enable better decisions. Design tools can select and push the most appropriate information from databases and multiple layers of data can be imported into a project at once.

Synchronicity: Multiple tasks that used to be performed in sequence can be performed in parallel. This can prove to be the main benefit but is the hardest to quantify in initial phases.

Figure 3 Illustration of synchronicity benefits of Automated Workflows

Initial business cases are typically based on software portfolio rationalization and migration to cloud solutions for data management. Pilot studies are then the best means of testing and quantifying the SES benefits.

OMV has linked an experience database to the design package. This holds all the hard-earned lessons of the previous projects and is easily to search with lessons linked to geological formations, depths, and wellbore sizes. The data can be displayed as plots and 3D displays making it easier to understand and contextualize. This database is rapidly updated after each well is drilled and shared across projects. This eliminates weeks of research and compiling by individual engineers and shortens the planning and design times.

The operational program is modular and broken up by design section. The program is automatically generated as soon as the design for a specific well is approved. Each module is reviewed after execution for possible performance improvements and updated. Wells are typically drilled in batched or campaigns. The ability to rapidly improve the operational modules can be used to drive performance significantly reduce costs.

Once the benefits have been identified then other internal cultural issues need to be managed. Senior management level usually recognizes the need to change, but change can be difficult as it takes time to realize the benefits of the various new technologies. Stakeholder mapping and communication is essential to keep the organization engaged.

Hierarchal organizations have evolved a series of controls and oversights to manage their business. There are often significant controls built around the internal transfer of enriched data (information) between departments/entities. Permission to transfer data from a department manager is required who would formally have had a QA/QC obligation – e.g., would have signed off a report or endorsed a spreadsheet. Allowing data to move seamlessly can be quite a significant challenge if the QA/QC responsibility remains with a manager or discipline that insists on a document sign-off. Recognition of task completion and quality assurance must occur within the digital environment. The team members have to own the task quality of a project allowing the digital workflow to be managed in an agile manner. Discipline middle management, who are usually the permission granters, can find this very challenging.

The other way to manage it is by the transfer of QA and Assurance responsibility to high skilled individuals recognized as Technical Authorities (TA). These individuals may have management responsibilities but are primarily seen as leaders and innovators within their discipline and are typically imbedded in major ongoing projects but have a percentage their time allocated to TA tasks.

Letting the Technical Authorities know when they are required and where to focus is managed by structuring the orchestration system to allow each model to be assured and reviewed within the workflow. OMV believes it also helps to make the orchestration displays look like game displays – i.e. tasks look like achievement levels and are color coded on progress. This makes orchestration more intuitive to new users and encourages better conversation on collaboration and data exchange.

The changes that Automated Workflow’s bring – like flattened management structures can add significant stress and resistance. Concerns about assurance, discipline guidance, scope creep and value creation /destruction all have to be made transparent and discussed openly. All these issues must be managed with constant communication and dialogue.

OMV conducted a series of workshops and consultancy sessions before building the digital workflows. Well delivery project management covers a wide range of project types from USD 150 mn deep-water wells to USD 2 mn onshore wells. A grand project that covers all possible types of wells and scenarios could take years to develop and be constantly prone to design creep. This is a common problem when looking at automation of processes. This can be overcome by narrowing down to pick some examples and maturing those in the expectation that the solutions can be generalized to apply to wider cases. This is often called the “use case” approach. OMV used filtering criteria to rank its islands of expertise, project frequency and cost. A “use case” based on onshore development wells became the company’s starting point. These wells were relatively low cost and high frequency but still required individual planning due to location and subsurface variability.

The Automated Workflow selected allowed the company to focus on the key engineering modules required and ensure they were ready. The inputs for modules from other software models became the driver for our system integration and over this OMV could construct its process orchestration. The first use case was a Smart Oil Recovery project on a large mature field. The Reservoir Engineering team members employ stochastic tools to build a three-dimensional model two kilometers below surface that changes over time. The best horizontal sections for wells are selected in the model. At the same time the well design engineers build a design envelope in an engineering model that is linked to surface locations based on road access and ownership. The reservoir sections targeted for production are pushed through to the engineering model where casing, fluids and rock properties are added, and the wells linked to the surface. There is a QA check to ensure that the wells are physically, and economically viable. If the QA checks are good then the program, construction diagrams and applications are generated. Any parameter in the models can be altered and the engines in the automated workflow instantly check against all the held variables. This means that the team members can work simultaneously which significantly speeds up the design time. The orchestration tool tracks changes and maintains version control so previous work is not lost and it is easy to revert to an earlier “best fit model” if required.

OMV found that once this use case was developed and proven – that the company was able to generalize its solutions and apply the automation framework to a wider set of projects. Some required further engineering modules to be matured – but the timelines were shortened, and the development time was reduced.

Automated workflows are meta tools that embed design and construction models and allow, what were previously sequential steps, to happen in parallel and critical workflows mature simultaneously. These tools allow models to be built using different data domains and have orchestration and data management capabilities. They are not conventional software tools that can be bought off-the-shelf and put to work immediately. The tools embed assumptions about how to perform a workflow and can drive the behavior of an organization. The tools have to be tailored to meet the requirements of the company and reflect the working culture that a company has evolved over time. Overall, OMV believes that this automation effort will have a major impact on the company’s development campaigns in terms of planning time and repeatability. OMV is rolling out this automated workflow in October 2021 for onshore production wells and offshore platform wells. The intention is to have the modules available for offshore subsea wells available early 2022 and the remaining cases covered by end 2022.??

Reference R Kucs, G Ripperger et al, The Journey for Digital Well Delivery Technology Adoption, 2021 Abu Dhabi International Petroleum Exhibition & Conference 16 November 2021 UAE, SPE-208143-MS