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Together we can improve production forecasting

Friday, January 8, 2016

Production forecasting is a critical task in the oil and gas industry, and is best if you have a mixture of complex modelling and the combined expertise of people from many different disciplines. Tom Fox explained how to do it.

Oil and gas asset managers need reliable production forecast information so they can take better decisions about how to maximise value from a well. And making better production forecasts needs a mixture of analytics and human expertise.

'Analytics are the key to understanding past production, but analytics alone fail to make an optimal forecast,' said Tom Fox, managing director of production consultancy 1234 Most, and a former consultant field development with Shell, speaking at the Digital Energy Journal Aberdeen conference on Sept 29 2015, 'Using Analytics to Improve Production.'

'A digital solution is an incomplete solution. If we leave out the people, that digital solution is probably useless,' he said.

Production planning is complex because it must reconcile three perspectives: commercial, production and maintenance.

Typically, these are three separate analysis flows which involve different expertise and diverse software, he said.

There are also uncertainties in both the modelling methods and the input data, so case studies are needed to assess a range of future scenarios.

Big data techniques, such as machine learning, offer a tempting shortcut to decision support, he said.

But if you skip the laws of engineering and physics, you can end up overloaded with false alarms mixed with false positives.

Engineering and maintenance models, calibrated by historical analysis, are essential to make valid predictions.

Need to be integrated

The Piper Alpha disaster is a sobering reminder of the human and commercial costs of management failing to make good decisions, due to weaknesses in the integration of complex activities Mr Fox said.

More than twenty-five years later, with low oil prices, we are once again under huge commercial pressure to keep production flowing, in order to defer asset abandonment costs. Therefore stress is applied onto maintenance activities - how to carry them out at minimal cost and with least downtime.

Complex decisions are especially prone to psychological decision traps. Sadly, we are not as rational in practice as we claim to be in textbooks and management courses, Mr Fox said.

The best antidotes to these psychological traps are collaborative decision-making and explicit recognition of the various forms of traps, he said, in some lessons taken from the 1999 book 'Smart Choices' by Howard Raiffa and Ralph L Keeney.

Collaborative decisions

Collaboration deserves purposeful investment of time, energy and money, Mr Fox said.

Everyone makes decisions, at all levels in the organisation and in all locations. When we involve more people in taking production planning decisions, the decision process must evolve to handle the increased complexity.

For example, instead of a binary yes or no, the gradients of agreement scale is a subtle solution to encourage greater participation in the decisions, as well as more reliable commitment to implementation.

"My vision is that we extend the decision-making and the analytics across the entire organisation, from the operators in the field to the management board room; that everyone can get a vision of how the operation works, how it can be optimised and that everyone can be involved in making the plans that implement efficient and economic production,' said Mr Fox.

One way to implement this vision would be to develop a collaborative business process for production forecasting, together with (probably web hosted) software which many people can use.

A production planning process

Mr Fox presented a production planning process based on a cycle of continuous improvement, which integrates expertise across the organisation from field operators to senior managers.

This process combines and integrates several proven techniques: 'Produce the Limit' workshops, multi - scenario planning, participative decision-making, delegation of responsibility to well-informed operators and quantitative 'After Action Reviews'.

With web enabled software, non-specialists can access analytics and modelling systems remotely. This way they can make a better contribution to the planning process and they can even experiment with their own ideas.

Analytics and optimisation together

To demonstrate that there is high, incremental value accessible from analytics and optimisation, Mr Fox presented a case study on the optimisation of gas lifted oil wells.

Faced with uncertainty in the future rate of gas lift supply, optimised field-wide solutions must be precomputed for a range of scenarios.

When compared with the base case (of what would be expected from a skilled and experienced operator) total oil production is significantly increased by using an advanced optimisation algorithm on numerous gas lift performance curves (obtained by analytics).


DynamicForecaster is a multi-user web application for collaboration on both production analytics and forecasting, developed by Mr Fox's company, 1234 Most.

It helps asset managers in upstream oil and gas companies who want to improve the financial return on investment, by using the insights from multiple users.

Asset teams can now make quicker and more varied analyses of past and future production, leading to better quality decisions and implementation. Further information is online at

Associated Companies
» 1234most Ltd
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