While E&P operators seek to tap new reservoirs in increasingly remote and more costly locations, they also are trying to drive their production costs down, in some cases, to under $7/bbl as one North Sea producer envisions. That goal requires technology to take over mundane tasks, such as data collection, collating and reporting, that workers used to do. It also necessitates a rethinking of basic operational functions, including power utilization.
Remote condition monitoring (CM) in a proactive, condition-based maintenance (CBM) model is one way to cut costs. Advanced lithium-ion energy storage solutions can reduce the run time of offshore platform diesel engines by an estimated 42%. In addition to extending the life of the engines, energy storage solutions can save diesel fuel costs and reduce engine maintenance requirements, while cutting NOx and CO2 emissions.
North Sea application
Remote CM collects operational data in real time from many hundreds of sensors on the rotating equipment, electrical equipment, instrumentation, automation controls, valves and process monitors of a wellhead. Although proven in a North Sea platform use case spanning 2016 to the present, the CM/CBM model can be deployed in onshore production as well.
The 60,000-bbl/d North Sea platform sits 180 km (112 miles) east of Norway and is monitored from a control room in Trondheim, Norway, 1,000 km (650 miles) away. The platform’s CM data are transmitted via secure, redundant links over a subsea fiber-optic network serving most North Sea E&P operators. Aggregate data are sent using ISO 27001/27002 and ISA/IEC 62443 security standards, the world’s strongest.
CM can be retrofitted to existing production assets but is easier to implement if designed into a production facility in the FEED stage. That was the case with the North Sea platform, for which Siemens was the prime contractor for electrical, instrumentation, control and telecom systems.
To implement a CM/CBM model, engineers combined diverse advanced technologies (i.e., smart sensors, fiber optics, data collection, storage and analytics, among many others) to conduct maintenance differently—not cheaper and faster, but better and smarter.
Proactive, predictive cost-saving model
CBM is a proactive maintenance model that eliminates maintenance governed by set schedules. Instead, maintenance is performed in response to monitored equipment’s operational state. If the equipment is operating within normal parameters with no signs of behavioral anomalies, its maintenance intervals can be extended. This reduces labor costs and capital tied up in spare parts.
Most importantly, CBM can preempt production disruptions by predicting and preventing them via mitigation and remediation. Artificial intelligence (AI) is instrumental in this. For example, should CM uncover possible trouble before a planned shutdown, the control room can start investigating causes and issue orders for preventive maintenance on equipment to avoid the costs and impacts of unplanned downtime or production slowdowns.
In fact, in an onshore remote CM pilot project involving electric submersible pumps in a 30-well field, an AI system detected an impending failure 12 days before its occurrence.
CBM enables the operator of the North Sea platform to perform maintenance in timely, wellplanned ways, reducing equipment downtime and disruptions. It also boosts safety by minimizing platform maintenance staff and the risks (and cost) in flights to and from the platform.
Remote diagnostic services for rotating equipment
CM-enabled CBM also can offer E&P operators remote diagnostic services for their rotating equipment, such as compressor trains, either single units or entire fleets spanning various locations, offshore or onshore. Although compressor trains are complex machinery, they are extremely fault-tolerant. However, should a fault occur, it can be expensive and even threaten HSE operational standards.
Using known parameters that define normal compressor operation, it is possible to program a compressor’s digital twin with all the required algorithms to identify behavioral anomalies. This can help avert trips and forced outages via early detection of potential faults and preventive remediation. It also can boost availability by as much as 3%, or about 11 days in a year.
This extra uptime over a compressor train’s typical 20-year lifespan can save significant costs in preventing downtime and related expense. Component life cycles also can be extended substantially, as a result of a more proactive CM/CBM maintenance model.
Energy storage solution cuts diesel engine run time
Another way operators of remote and low-manned well operations can boost efficiencies, lower costs and cut emissions is to employ lithium-ion energy storage at scale.
For example, offshore rigs have highly variable power requirements for drilling and their dynamic-positioning thrusters. By adding an energy storage solution to the rig’s power supply and distribution systems, rig operators can reduce their diesel engines’ run time yet operate them at optimized combustion levels to save fuel and emissions.
In 2018 Siemens announced the deployment of its BlueVault energy storage system on the West Mira drilling rig that will operate in the North Sea’s Nova Field. This will be the world’s first drilling rig to operate a low-emission hybrid (diesel-electric) power plant using lithium-ion energy storage.
The solution consists of four converter-battery systems that can deliver a total power of 6 MW. Charged by the rig’s diesel-electric generators, the batteries will supply power during peak loads. They also provide backup to prevent blackouts and power the thrusters in the unlikely event of loss of all running machinery.
The installation of this low-emission hybrid power plant on the West Mira platform will reduce the run time of on-platform diesel engines by an estimated 42% while cutting CO2 emissions by 15% and NOX emissions by 12%. These estimates are derived from the operating knowledge of having deployed similar hybrid power plants on more than 60 maritime vessels worldwide.
Keys to the future
To operate more profitably and sustainably, remote and low-manned production must deploy advanced technologies to enhance the electrification, automation and digitalization of functions otherwise performed by inefficient machines or workers.
This increases operational transparency and responsiveness to maintenance issues by reducing the latencies from time-consuming and error prone manual data collection, normalization and reporting. In addition, operational disruptions and HSE risks can be reduced, if not eliminated.
The sooner E&P operators deploy these technologies, the sooner they can realize the benefits and investment returns. Plus, early adopters of these kinds of proven technologies will have a competitive advantage over those preferring the status quo.
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