How companies can reduce cycle times during prospect evaluation

Finding and eliminating bottlenecks in the hydrocarbon exploration process.

In recent years the E&P industry has been beset by notorious delays. From cross continental pipeline construction to offshore drilling projects, environmental, legal, and political factors have repeatedly extended timelines, sometimes by years. Many of these perils are unavoidable in the high stakes world of hydrocarbon extraction. However, there is one bottleneck that organizations can control - their own prospect evaluation cycle times. While the external problems grab the headlines, organizations can achieve significant gains merely through internal process improvements. In my conversations with E&P leaders, two interrelated concepts surface repeatedly as ways to reduce cycle times: stronger integration of existing processes and empowerment of asset teams with better science.

Lack of data integration and software compatibility was cited as the top bottleneck by respondents in research conducted by Welling & Company last June. They interviewed 249 geoscientists and engineers working globally. The survey spanned the entire prospect evaluation workflow: processing, interpretation, modeling, and simulation.

The impact of this lack of integration is clear to see. The survey indicates that a fifth of the time spent in prospect evaluation is spent just managing data. About two-thirds of the time is spent on geoscience analysis and risk evaluation. The remaining portion is spent on presentation of results. The evaluation time for a new field is about 24 months. This means almost five months of productivity is lost just managing and validating the data! For large independents, who spend an average of 35 months evaluating new prospects, this ratio amounts to a staggering 7 months in lost productivity. Now multiply this impact across all the prospects an organization is evaluating each year.

Some organizations are regaining a portion of this lost effort through internal process changes. Many data management woes arise from the age old issue of disparate teams working in silos, using non-integrated tools, and tossing data back and forth over the wall. This slows down the workflow, introduces more data to manage, and creates less accurate results due to data conversion requirements. However, organizations are working towards eliminating this bottleneck by incorporating cross-connectivity solutions like OpenSpirit which allows data to be easily shared between systems. At SMT, we partner closely with OpenSpirit to help so many of our customers that face this challenge. In the months ahead we will be working with them to take our cross-connectivity capabilities into the next generation.

While software interconnectivity is important, just as important is the need to empower all asset team members with the full range of decision making tools. Too often in organizations that I speak with, the prospect evaluation workflow is carved out and distributed to specialized resources. While specialization is necessary to create internal expertise, it should not come at the cost of curtailing the abilities of generalists who can understand the workflow as a whole. For example, in many organizations pre-stack work is done only by specialists using their own tools. Therefore generalists do not conduct any pre-stack analysis in their own work and do not see the pre-stack data which often provides very clear hydrocarbon indicators.

Similarly, many organizations restrict reservoir modeling only to reservoir engineers. Yet geoscientists can also benefit from sealed earth model creation, property distribution, and volumetric analyses. Here again the barriers of disparate teams and nonintegrated tools lead to bottlenecks that lengthen the cycle times. Organizations I have spoken with say that in many cases, the geoscientists' interpretations are altered by the engineers' modeling, causing some loss of integrity, and resulting in the need for re-interpretation. This cycle can repeat itself over a dozen times before the evaluation can be completed.

One way to solve this problem is to bring specialized science down to the generalist and push advanced capabilities onto every desktop. At SMT we have tried to achieve this goal by allowing interpreters access to pre-stack and post stack data, geological and geophysical analysis, and soon, interpretation and modeling, all in one place. The objective is to enable all involved personnel to see the full picture, while retaining experts for the most difficult cases. We believe this approach can help asset teams reduce prospect evaluation cycle times by reducing confusion and increasing collaboration.

However, achieving process change in organizations is difficult work because it often requires significant shifts in outlook. But a company must ask the question; in the uncertain marketplace the industry faces today, can we afford to give up five months of cycle time just to manage data?