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Technology promises greener operations at sustainable cost

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Pål Rylandsholm Pål Rylandsholm
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environmental monitoring and modelling
Photo: DNV GL
A guideline for designing environmental monitoring and modelling systems makes cost efficiency a key criterion

A pan-industry technological revolution is underway, according to Remi Eriksen, Group CEO, DNV GL. He sees the world entering a renaissance in industrial progress through accelerated uptake of cyber-physical systems. “Concepts such as automation, data-driven insights and grid parity will acquire real meaning and scale over the next decade,” he said in introducing DNV GL’s latest report on where technology trends are leading.

These include developments in oil and gas. Digitalization, connectivity, automation and remote operation are key themes in considering the potential of rigless plugging and abandonment of wells, autonomous pipeline inspection, and fully automated drilling operations, for example.

Digitalization and connectivity are already having a meaningful impact. One example is sensor-based systems for environmental monitoring and modelling (EMM). Real-time online data, and greater use of modelling, are part of this. These systems provide deeper insight into site-specific oceanography, ecosystems and the fate of operational discharges such as drill cuttings.

Norway is a leading user of sensors to monitor sensitive species such as cold-water corals. “EMM will play an even greater role in future, particularly for greenfield developments in ecologically sensitive areas,” predicted Trond Austrheim, vice president, R&T facilities technology at Norwegian operator Statoil, which has been committed to EMM for several years.

Most current EMM systems collect data, but offline and only for documentation purposes. “However, I think the industry will increase adoption of online EMM, as it provides more real-time information,” Austrheim predicted. “In some cases, especially in more environmentally sensitive areas, it can be integrated into operations to provide a better factual basis for understanding risk and how to mitigate it.”

Environmental monitoring and modelling, graphic by The Big Partnership
Graphic: The Big Partnership

Online monitoring in action
Online underwater cameras and sensors deployed during drilling in the Statoil-operated Hyme oilfield and Morvin subsea field documented in real-time what was happening in a sensitive area near cold-water corals, for example.

Statoil encourages supply chain companies, academia and other oil companies to work jointly with them on research and development (R&D) projects such as the LOVE ocean observatory programme, helping to push development of online EMM technology and models in Norway.

“There is debate in Norway about opening up sensitive areas for oil and gas developments. The sensors being deployed will enable fact-based discussion of risk and its mitigation,” Austrheim explained.

A guideline for EMM design
While the environmental performance benefits of EMM are clear, the industry lacks standards for designing and implementing such activities. Statoil and DNV GL have collaborated therefore to develop a guideline, proposing an approach for conceptual design of robust EMM systems that, importantly, is also cost-efficient.[1]

The module-based guideline (refer to infographic) uses evaluation criteria established by defining the challenge; which decisions need support, and the data required; the area for monitoring, for how long and how often; data analysis needs; and the acceptable level of uncertainty for data accuracy.

The selection process for three system designs for an EMM programme related to the discharge and environmental fate of drill cuttings is illustrated.

This approach involves steps that translate into hardware and software requirements. Austrheim hopes that the industry’s familiarity with these steps from other technology evaluations will lead to wide and easy implementation of the EMM guideline. “It is offered as an industrywide approach that would allow us all to evaluate EMM hardware and software in the same way. This would broaden and compare experience with these systems.”

Normally, several EMM system designs will meet the requirements specified. Cost efficiency is included therefore as a key criterion for making the final selection.

Operational expenditure (opex) is high for traditional, offline EMM programmes because of vessel rates and labour costs offshore and in the laboratory.

Capital expenditure is higher for online EMM, with hardware for a greenfield development typically costing around USD1 million, Austrheim said. “However, you can potentially get payback on hardware by saving on vessel time,” he added.

Operating costs
Currently, maintenance constitutes the highest opex element of environmental monitoring and modelling systems. Furthermore, reliable data transfer from subsea hardware is among the challenges for online implementations of EMM.

Transfer quality can vary, particularly so during oil and gas exploration activity in remote and deepwater locations, in harsh climates, and where there is no existing infrastructure.

However, opex remains low compared with offline EMM systems that require vessel time and large numbers of personnel for baseline and follow-up environmental surveys.

Online data collection
Where consistent online data transfer is difficult, operators could reduce cost by using a rig-based, remotely operated underwater vehicle, or a standby vessel’s spare time, to achieve data transfer on demand.

“Online, sensor-based approaches can also improve decisions on whether or when inspections and/ or interventions are needed, which increases cost efficiency as it helps to avoid downtime,” Austrheim added.

He concluded with a call for action to refine the use of EMM: “Reliable monitoring systems such as LOVE already provide volume, quality and reliability of real-time data streams. Some environmental data analysis tools are sufficiently developed, but more R&D is needed to generate better models for improved decision support.”

[1] ‘Guideline for design of cost-efficient and robust sensor based environmental monitoring systems’, A Ulfsnes et al, SPE International Conference and Exhibition on HSSE and Social Responsibility, Stavanger, Norway, April 2016

Disclaimer: 

DNV GL prides itself on providing accurate information but makes no claims or guarantees about the accuracy, completeness or adequacy of contents in this publication, and disclaims liability for any errors or omissions. The authors’ views here do not necessarily reflect DNV GL’s views.