Big Data in the O&G Industry
What do you understand by big data?
Big data is the challenge that many industries, including oil and gas, face in handling large volumes of data and information, much of it diverse, unstructured, and increasingly real-time. When harnessed properly, big data is a big opportunity, offering enormous value through improved knowledge and decision-making.
Why is it so important to E&P?Ahmed Hashmi, Global Head of Upstream Technology, BP.E&P is an intensely data driven, high technology business; it always has been, particularly in the subsurface. The data and knowledge we have about the fields we operate today, and from others in our past, inform our future developments, as well as providing analogues to other fields for new access.
In operations, control of big data offers improvement in safety, efficiency and reliability: today our operational environments are enabled with hundreds of thousands of sensors, each transmitting performance data against a defined operational envelope, enabling us to adjust, optimise and increasingly to predict anomalies before they arise.
What are BP’s big data plans?At BP, we have publicly stated our ambition to be the leading digital upstream company. Harnessing the power of data is key to this ambition. Over the past decade we have invested in subsea fibre to connect our operations to our centres of expertise, in high performance computing to crunch through massive volumes of subsurface data and in a proprietary data lake. Every day, twice as many data records enter the BP data lake than daily tweets on Twitter – and we plan a six-fold increase by 2020. We are building the Connected Upstream – connecting up our equipment, systems and people. It is BP’s Industrial Internet of Things.
What is driving these plans?The E&P sector faces many challenges today, not least the lower oil price. There is still short- and long-term demand for oil and gas: the world needs our products, but it wants lower carbon energy, and renewables are now presenting a real alternative. The economics of our industry have changed – we need to adapt to succeed.
Building the Connected Upstream and becoming the digital leader in our sector is part of our strategy to transform, and become more efficient, more resilient and create more value for our shareholders.
Is the industry technologically at the forefront of big data?As a sector, we can often appear to be digital laggards. But there are pockets where we have moved further and faster than almost every other sector, including high performance computing. We have continuously invested in compute power over the past two decades to underpin our seismic processing capability. BP’s Centre for High Performance Computing is equipped with six petaflops compute capacity, and growing. Today, we run complex seismic algorithms in a week that would have taken us 2,000 years about 20 years ago.
But while high performance computing is an acknowledged leadership area, in other areas we are building capability. For a long time our sensors were transmitting more data than we could handle; that is changing, with platforms like Plant Operations Advisor, a collaboration with GE using its world-class Predix systems – the first application for our industry. We have built a proprietary capability, using Distributed Acoustic Sensing with downhole fibre, to record sounds within our wells two miles below the seafloor to listen for sand which can constrain our ability to produce oil. Each hour we record a terabyte of data: the equivalent of downloading 1,000 Netflix films simultaneously. Today, not only can we record those data, but we can extract what’s valuable, visualise them, and make decisions from them.
So the answer is, yes, we’re at the forefront in some areas, and catching up fast in others.
Will big data and cloud computing change the industry?Big data – when coupled with the cloud, machine learning, AI, automation and even higher performance computing – is a big opportunity, but we need to be realistic. Right now, there is a lot of hype around digital, with claims of exponential value; 10x rather than 10% improvements. Delivering anything close to this magnitude of improvement will require the industry to throw out the rule book. It will need novel technology collaborations, fresh thinking around some of our established ways of working across the industry, skilling up our people in advanced analytics and getting our mindset to one of balancing physics-based approaches with data-driven solutions.
Digital is already changing our industry; those who seize the opportunities it presents are likely to adapt best, become more resilient and create more value.
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9 Big Data Applications
As the use of Big Data is increasing, the industry application is getting lower and lower. Very often, we will see some very innovative use of big data in improving our daily lives in many ways. How do we make use of Big Data in order to extract valuable insights from it and use it to or advantage? We will examine the 9 Big Data applications that are known to us today:
1, Big Data is improving our lives
Big data is not just about businesses and governments, but also for individual like us. The wearable devices that we use capture a lot of good data about our daily lives, which can help monitor our health, lifestyle, activity, sleep pattern and quality, emotion and state of mind, and these data can be used to suggest improvement for us to live better. These data can even be used in finding our compatible partners in dating websites.
2, Business Process Optimisation
Big Data also helps to optimise business processes. This can be achieved through the use of social media data, web search and weather forecast to dig out valuable data, which is the most widely used in optimising the Big Data supply chain and distribution channels. In both of these areas, geolocation and wireless tracking of goods and delivery vehicles, using real-time traffic route data to develop a more optimised distribution / delivery network
3, Understand the customers and their needs
Currently Big Data is most widely used in this area. The focus is on how to use Big Data to better understand the customers, their interests and behaviour. Companies are very keen in collecting social data, browser logs, analysing text and sensor data, in order to better understand the customer. In most cases, data modellings are developed to perform predictive analysis. For example, the famous US retailer Target, through Big Data analysis, get valuable information to accurately to predict when customers want to have children. In addition, through the application of Big Data, telecommunication companies can better predict the reason for losing customers, Wal-Mart is more accurate in predicting when and what products will be selling well, the car insurance industry can better understand the needs of customers and driving skill, the Government can better understand voters preferences.
4, Improve Sports Performance
Today, many athletes under training are using Big Data technology to analyse their performances for corrective measures, Such as the IBM SlamTracker tool for tennis matches. We also use video analytics to study the performance of each player in a soccer or baseball game, and sensor technology in sports equipment (such as basketball or golf club) allows us to obtain data on the game for future improvements. Many elite sports teams also track the activities of athletes outside their sports lives - by using smart technology to track their nutritional level and sleep quality, as well as social dialogue to monitor their emotional status.
5, Improve Medical Research and Development
The computational power of Big Data analysis applications allows us to decode the entire DNA in a matter of minutes and enable us to develop the most effective treatment program. It also allows us to better understand and predict diseases. Big Data technology has been used in hospitals to monitor the condition of preterm and unwell babies. Through recording and analysing the babies heartbeat and other data, the doctor can predict when and where babies will feel discomfort and provide early treatment to ensure safe delivvery of babies.
6, Financial Transactions
Big Data in the financial sector mainly applies to financial transactions. For example, High Frequency Trading (HFT) is an area where Big Data algorithms are used in conjunction with social media interactions and website news feed to reach transactional decisions in executing a buy or sell decisions in near real time.
7, Improve Our City
Big data is also being used to improve the quality of our daily life in the city. This can be in the form of safer and smoother traffic condition for road users due to optimised operation of traffic lights based on analysis of real-time traffic data, social media interactions, and weather data.
8, Improve Security and Law Enforcement
Big Data is now widely used in the process of security enforcement. We all know that the US Security Agency uses Big Data to predict possible terrorist attacks, and even monitors the daily lives of people with suspicious bahaviour and activity. companies use Big Data technology to defend against network attacks. Police use Big Data tools to help arrest criminals. Credit card companies to use Big Data tools to predict and alert possible fraudulent transactions.
9, Optimise the Performance of Machine and Equipment
Big Data analysis can also make machinery and equipment to be self learning and operating more intelligently and autonomously. For example, Big Data tools have been used by Google to develop its driverless car. Toyota's Prius hybrid car is equipped with a smart camera, GPS and sensors to make the car to be able to drive more safely with minimal human intervention.
Big Data applications do not just stop here. The fact is that - how we can make meaningful use of Big Data is only limited by our own imagination and creativity. Otherwise, be prepared to see more innovative Big Data applications.
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