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2016 Oil and Gas Industry Predictions

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In 2016, the oil and gas industry will jump on the opportunity that big data presents: machine-learning strategies will become ubiquitous as oil and gas companies start rolling out condition-based maintenance; meanwhile equipment suppliers will move increasingly to a services-based business model. Equipment manufacturers have begun to embed machine-learning technologies into equipment for condition-based maintenance,

to help customers extract maximum value and efficiency from their infrastructure.

These suppliers are looking to provide support services such as data monitoring, which will help customers optimize equipment utilization and maintenance strategies, and will also provide data that can be used in the design phase of new products; for example, with enhanced user data you can improve the precision of your design parameters, thereby optimizing the product cost and value relationship.

This marks a turning point in the business strategy of the suppliers as oil and gas companies have been hesitant to rely on the equipment suppliers to run maintenance programs due to fear of vendor lock-in, which would push up costs, but they see the benefit in gathering data from their installations to improve operations.

Hence, increasingly, oil and gas companies are looking for ways to own the data they generate and technology that enables them to manage the condition-based maintenance programs.

In the next twelve months we’ll also start to see this become a reality as more oil and gas companies take steps to capture and learn from big data to make their operations smarter and reduce costs.

The businesses that will be successful are those that develop a strategy to underpin this – to benefit from data, they need to understand what data they are collecting, how to categorize it, what insights they will gain and how to turn this into tangible benefits e.g. cost and time savings.

With this in mind, the more advanced businesses in 2016 will have automated learning up and running in their machines so that they can replicate the best results their businesses are seeing across their operations and benefit from experience across the entire organization to increase productivity and performance.

3D printing will emerge as an innovative alternative for companies in the oil and gas industry in 2016, as they scrutinize their supply chains and engineering practices.

A small but increasing number of businesses are already deploying 3D printing technology and using 3D printing in two different ways:

Firstly, to create models that can be used for training purposes. Innovation in training methods has been driven by the need to move away from on-site apprenticeships due to a mixture of safety issues and new technology requirements in the field that have changed what is practical to teach on site. Hence 3D printing is becoming particularly valuable in teaching onsite equipment repair and maintenance; particularly for offshore and subsea equipment.

Secondly, businesses are using 3D-printed tools and parts as replacement for traditional tools and parts, helping access and maintain equipment in remote areas. These parts and equipment that could be printed include almost anything that can be drawn in 2D, eg, drill bit molds, actual fix cutter drill bit bodies, and other down-hole tools.

Although oil and gas is traditionally a more conservative industry, technological developments that enable businesses to cut costs and improve performance and asset integrity are beginning to be rolled out in maintenance and operations due to necessity.

The driver that will push this into place in 2016 is the drop in the price of oil.

Previously oil prices were high, so businesses were able to continue using technologies and techniques that had served them well for several years. As the price of oil has now dropped, oil and gas companies are looking to streamline costs and increase efficiencies where they can.

They are looking for smart ways to cut costs, and 3D printing is proving an enabler for this right across the supply chain from inventory to transportation.

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