The ever-growing industrial challenges that are faced by oil and gas industries can be surmounted by the insights produced from the large amounts of data produced by these companies. The challenges might usually be poor visibility in complex operational activities, issues in logistics, meeting environmental regulations, management of equipment lifespan and issues in performance improvement.
Today, we’re going to share some information with you on how to use the big data analytics to your benefit in the oil and gas industry. But before you start this article why don’t you quickly go through these two fun reads about practices to implement left-shift approach to testing and salesforce sales cloud certification.
Big Data Analytics and Oil and Gas Industry
The big data analytics help with streamlining operations in three sectors, which are: upstream, downstream and midstream.
Experts note that big data solutions can be employed in the following areas in the upstream sector.
- Seismic Data Management: An area of interest with potential petroleum resources is scoured for seismic data when upstream analytics begin. The data is collected, processed and then analyzed in order to pinpoint the location for drilling.
The seismic data can be combined with other sets of data to determine how much of gas and oil there is in the location.
- Drilling Process Optimization: Customizing the predictive models, which forecast future equipment failure is one method of optimizing the drilling process. In the start the equipment is fitted with sensors when it is used in the drilling. This data along with other metadata of equipment is run through algorithms of machine learning to find out the usage pattern which will lead to a breakdown.
- Reservoir Engineering Improvement: The production of reservoirs can be improved when various kinds of downhole sensors are used. The companies can develop apps which will inform them timely about changes in the reservoir so that they can take proper action promptly.
One major concern in the oil and gas industry is the logistics. The safe transport of petroleum resources without any risk is very important. Companies use sensors to make sure that their product is safely being transported. Maintenance software programs which can detect and predict abnormalities in the tankers and pipelines so that accidents can be prevented are also utilized.
To reduce the cost of maintenance and the cost of refining equipment, the petroleum enterprises can bring to use the predictive analytics of big data. This improves asset management. The first thing is to find out how the equipment operates currently in comparison to the past. The performance estimated from the equipment is visualized and shown to the specialists. They then make the final decision about maintaining and replacing them.
To persuade you further let us give you an example of the famous petroleum company, Royal Dutch Shell PLC, uses big data analytics in their operations. The following are a few ways:
- In surveying and monitoring areas for exploration petroleum.
- In forecasting petroleum production.
- In increasing the life of the equipment.
- In improving the efficiency of logistics.
- In reducing carbon footprint.
Big data analytics can be of immense use to oil and gas industries when it comes to cutting back on operational costs, improving equipment lifespan, reducing the harmful environmental impacts and making other sound decisions.