Anyone who has watched a Formula 1 (F1) racing team in action might have wondered why so many people in the pit spend so much time staring intensely at computer monitors. The answer is telemetry – a word derived from the Greek tele for “remote,” and metron for “measure.”

Out on the track, the race car is wired to stream information on every physical attribute of the vehicle back to the pit crew. Engineers staring at those screens are processing and analyzing data moment by moment, anticipating critical decisions they need to make to win the race.

What does E&P have in common with racing?

F1 racing is a vivid and dramatic analogy for what takes place in E&P companies all over the world. In the global pursuit of hydrocarbons, real-time workflows are becoming prevalent. Just like F1 cars, modern oil and gas fields bristle with instruments that beam a constant stream of digital data from deep below the earth all the way back to the office.

Understanding complex subsurface physical conditions has become increasingly difficult. It requires specialists from multiple disciplines to strive for greater collaboration to locate and extract precious fluids and bring them to market from remote areas of the world. Today’s asset team is an F1 pit crew, responsible for processing and interpreting all these data and turning them into useful information in real time. For both teams, the ultimate objective is the same: to enable faster, better decisions that maximize return on investment.

To take the analogy one step further, an F1 pit crew can use the live data feed to advise the driver when to make tactical “on-track” adjustments. Similarly, office-based geologists and drilling engineers can monitor real-time log data during geosteering operations and instruct the directional driller to make course corrections when necessary.

F1 racing teams also use real-time data to make more strategic decisions. For example, they must determine when to bring the car into the pits and adjust the settings necessary to achieve optimal performance. E&P teams also make strategic decisions based on new data. They must anticipate when to pull the string out of the hole and change the drill bit, when to alter the mud weight, or even when a new ahead-of-the-bit well plan should trigger an update of field models and maps to ensure safer, more successful outcomes.

For either team, success depends on more than just the simple acquisition of real-time data. It requires efficient data management, processing, analysis, and interpretation systems that enable a diverse group of experts to work together and make smart decisions under extremely demanding conditions.

Realizing the full value of real-time information

Consider what it takes for a team to make joint decisions using real-time data. Data at the rig must be acquired, formatted, and transmitted to the office. There, data must be received and made available for analysis and interpretation to transform the raw data into information that the team can use to make decisions. Two basic alternatives exist for the storage of such valuable data.

In the first alternative, multiple feeds or copies of data can be routed into individual standalone applications, which each team member with a particular area of expertise then uses to perform a specific evaluation. The second alternative is to capture real-time data in a single multiuser data store and provide expert analytical tools in a unified, multidisciplinary desktop application that can access this shared database. In the first alternative, experts get a copy of the data in their own application. In the second, data that are stored once are available to the entire team.

Working with a copy of the data may seem pragmatic because users have their own version on which to experiment, giving them creative freedom. The downside is that the results of their analyses become stranded in isolated application databases. This stifles collaboration with other members of the team or requires them to perform multiple data transfers between all these standalone tools. This process wastes precious time and introduces the risk of data corruption, loss, or duplication.

A common desktop environment with a shared database also provides team members a more efficient and collaborative workspace than any set of standalone systems.

Real-time subsurface updates

To understand what is being drilled into, typically maps and models of the subsurface are made based on data from previous wells and seismic data acquired over the study area. The traditional process of creating these maps is too time-consuming and labor-intensive to enable asset teams to update in real time.

In the left image, reservoir fluid contacts update to show how the area transforms as new data are added in real time. In the center image, a cross section through the prospective fault block shows the model before (dotted lines) and after (solid lines) the dynamic data updates. The right image shows the Dynamic Frameworks to Fill geologic fault terrace framework with fluid-filled reservoir compartments automatically detected.

Some asset teams take the time and effort to generate a full 3-D geocellular model, which allows them to integrate and spatially distribute subsurface rock property information or investigate a range of stochastic realizations of earth model properties. While they can plan new well locations based on this kind of modeling, this fastidious and comprehensive approach has significant drawbacks. For one thing, it is not unusual for geocellular modeling to take weeks or months to complete, which is the antithesis of real-time decision-making.

The real-time revolution is essentially at odds with traditional techniques in the same way that electronic communication has basically made letter writing obsolete.

A new alternative, the DecisionSpace Desktop, is now available to upstream asset teams. This dynamic 3-D “framework” modeling system has an advanced topology engine at its core, which allows the team to automatically create structure maps that are consistent from one reservoir level to the next.

Each map surface within the framework contains the instructions required to generate the surface input interpretation, surface interpolation algorithm, extent, and geometry of the grid. The topology engine tracks the relative position of and relationship between every surface and fault that shares an intersection or touch point. Geological rules re-execute automatically whenever new data or interpretations affect linked surfaces. This “dynamic” approach represents a dramatic departure from conventional mapping workflows. Asset teams can easily incorporate real-time data and instantly update every map, fault, or unconformity within the 3-D framework. Real-time updates apply equally to interval property maps as long as teams establish instructions to automatically populate the framework with relevant properties using the new Dynamic Frameworks to Fill capability.

Ensuring superior performance

Real-time operations have begun to accelerate decision-making processes across the oil and gas industry. At this point, however, the industry is only scratching the surface of what is ultimately possible.

Just like modern F1 racing teams, upstream asset teams will soon come to rely on real-time workflows and collaborative, automated systems in order to shift gears fast enough to ensure both safety and superior oilfield performance.

Comments