Role of Data in Optimising Lease Bidding for O&G Industry
Published on : Friday 06-12-2019
There are three very clear risk factors before any company that decides to lease fields for oil exploration and rigging, says Siddhartha Ray.
The highly unpredictable Oil & Gas industry has always been a hotbed of uncertainties. The fact that companies need to bid for multi-year leases for exploration and drilling rights, without any certainty about the profitability of the enterprise, makes it even more risky. While the price for these needs to be paid as per the present cost to access a future profit, the base of these calculations could be very volatile.
However, the sector generates a huge amount of data that could be structured and analysed to enable better, more insightful and better-informed decisions. According to McKinsey estimates, the O&G industry today has a $200 billion performance gap. On the same lines, a recent research paper from DNV GL estimates that if the O&G could analyse and understand all the data from its production processes, the insights could help to boost operational efficiency by 20%.
The risk factors
There are three very clear risk factors before any company that decides to lease fields for oil exploration and rigging.
Political Risk
This risk could be regulatory in nature but more often than not, it has to do with the political volatility in a geographical area. Policy decisions control how, where, why and when oil exploration and extraction can be done. These depends on a number of things but a big factor is the political situation of the country or area.
Typically, an oil and gas company is covered by a range of regulations that limit where, when and how extraction is done. That said, political risk generally increases when oil and gas companies are working on deposits abroad. There have been many instances where a contract that started with a set of agreements and bye laws, changes with the political machinery. There could be a sudden change in nationalisation to suit domestic policies, and there is always a risk of instability in governance as well – a coup, a dictatorship or a war even.
This needs a careful analytical evaluation of the political climate, policy trends and building sustainable relationships based on data points of historical movement.
Geological Risk
The geological positioning of the proposed exploration and lease site also plays a key role in the risk. The area could have exhausted its resources, or could be on a platform far out in the high seas or could have already been squeezed dry. The new lessee would have no way of knowing these. Oil and gas geologists have a constant system of testing for reserves, and they rely on this data to predict the risk or lack of it, before a lease is drawn up.
Price Risk
The cost of extraction and drilling could also be less than profitable, without the correct data. That is specially so in an inhospitable environment which demands higher technology aids for working on. With the data they have, an analysis can help identity the pricing trends and thus the likely prices trend can be forecasted. This will help to decide the probable profitability of a project. But even with these projections, the risk is a constant! Given the high costs of operations and setup, it is not easy to shut down as a response to the price risk.
Technology can help in most of these situations, by efficiently analysing the parameters using the right data analytics apps. This data could assist companies in making informed decisions for leasing or passing up an offer, very often becoming the critical difference between a profitable investment and a catastrophe!
The benefits of Big Data and analytics
According to estimates by McKinsey, even a ten per cent improvement in production efficiency can result up to $220 million to $260 million bottom-line impact on a single brownfield asset. Leveraging Big Data analytics to improve efficiency could be the best way forward for companies in this sector. The research paper from DNV GL says that 16% of O&G industry experts believe that using Big Data analytics will have the biggest impact on operational efficiencies in the industry.
Safeguarding Investment decisions
Data collated from various sensors, earlier explorations and other sources could be the best aid for insightful decisions on lease bidding or extract accurate yield predictions as RoI, helping in predictability of the yield from exploration of a particular field, before investments go into it. The analysis of a number of data points – seismic, drilling, and production data – could help engineers map the trend of changes in the reservoir, and help in decision support. Incremental differences in these data points can actually drive huge profits or losses. It could help in accurately judging the bidding price, and also deliver a high value well at a lower bid price for some.
Meeting Geo-Political Challenges
To mitigate political challenges, companies like Datarama and Geoquant use analytics and AI to provide deep insight about the political moves and trends. Arming companies with higher-level data-based insights, they assure some predictability in the constantly shifting stands of the oil and gas industry of a country. Similarly, analytics can be used to assess the geological situation better by analysing the huge data that is gathered from sensors, seismic activity and other touch points. This helps mitigate the risks for a new entrant.
Predictive Maintenance
Data Analytics could add hugely to the savings and risk mitigation, by historically identifying the risk factors and how such incidents can be prevented. With the predictive analytics insights, the traditional approaches of either waiting for a fuse to blow, or waiting for the warranty period of the parts and the AMC contract to end- can be avoided in favour of a far more efficient predictive system. It could be a big risk in terms of security or something as small as a component that needs replacement. Predictive maintenance studies the data from all parts and derives the historical analysis of the wear and tear of the parts based on actual performance. A data based predictive plan could help save costs, minimise downtime and also boost efficiency in upstream as part of the oil and gas business process.
Moving beyond the risks, data analytics and AI can be invaluable in a number of other activities related to oil exploration and yields as well as leasing bids. The insights could be the game changers in improving business outcomes for the oil and gas sector. In addition, there are a number of activities that can be made smarter faster and more accurate using analytics and AI – production optimisation that could help to analyse seismic and subsurface data faster and predicting oil corrosion risks, to name a few.
The Bottom Line
The oil and gas companies have more than their fair share of risks and insecurities on the leasing bid decisions. Effectively using Data and analytics, along with AI, can be the biggest decision support for bidding activities for lease in oil and gas industry.
Siddhartha Ray, Delivery Manager, Hi-Tech Vertical, QuEST Global, has 17 years of experience on client-server applications, ERP package implementations and BI solutions. Siddhartha’s major focus areas is new age BI and Machine Learning platforms.
How Big Data helps
A major Fortune 500 oil and natural gas exploration and production company operating thousands of wells onshore in the US and Canada wanted to provide stable, environmentally responsible production of over 500 thousand barrels of oil equivalent per day.
The site managers collected large volumes of granular sensor data about well depth, gamma readings, etc., but since it was fragmented across site locations and spreadsheets, they couldn’t derive an easy way to correlate it and derive insights on practices that would yield the best results across different geographical areas. But using Big Data analytics tools, the business analysts were able to identify the highest performing wells and also the reason for their efficiency. The production team used these insights to develop a new well design that is now is contributing to a 60% increase in well performance, adding to annual production by over $100 million per year.
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