For the oil and gas industry, reducing cost and improving efficiency have become critical focus areas as commodity prices continue to push to levels not seen in the industry for several years. Where prices are going to bottom out, much less when they rebound, is anybody’s guess. What isn’t in dispute are the difficult decisions companies are being forced to make as debt concerns, hedging realities and operational pressures are pushing some executive teams into decisions that will impact how their organizations plan and execute projects going forward—particularly with onshore well development projects.

As organizations weigh whether to cut head count (and how much) or to continue drilling while delaying completions, these decisions made now will have ramifications for future capex. To identify the best alternative, leaders and asset teams have always sought access to critical data to help drive better decision-making and better planning. In the past, access to critical data, particularly offset well data, was often difficult to obtain, missing key elements or simply too much of an “apples-to-oranges” comparison to derive meaningful and credible insight.

Today technology is allowing organizations to pull information from multiple sources in such a way that key data and insights can be pulled from multiple locations depending on how search fields and parameters are defined. Data are abundant and available for analysis, key performance indicators (KPIs) and credible conclusions.

Competitive baselines
The opportunity for operators today in leveraging data availability is not so much in optimizing a specific function but in taking data to drive an integrated design, planning and execution system to realize competitive programs. This is key because, at the end of the day, organizations are competing for investment dollars.

Investors are looking for organizations that can competitively differentiate themselves from other offset entities through cost, performance and returns. The right degree of integrated planning can minimize nonproductive time, as an example, especially in the handoffs from drilling through first production.

If an operator is going to maximize the value inherent in its acreage and, by extension, design an externally referenced program, it must have an idea of the competitive profile of the given basin or play. This is essentially a starting point for design. Each basin has a competitive profile that can drive an optimal well design.

The role that data, or greater data availability, can play in this is to allow organizations to develop a pool of operating information from offset wells. This can include drilling data (days, costs, other), completion data (days, costs, other) and facilities data. That pool of information can then be used to create a composite well that highlights what competitive performance looks like in a specific area serving as a baseline or foundation that reflects the best of what can be achieved in a particular basin that designing and planning assumptions rest on.

Design and planning
Given that the composite well data reflects the potential inherent in each basin, that quantitative foundation can be used as a basis to begin reverse-engineering a program. Determining the difference between internal objectives and externally referenced competitive basin performance can then allow an organization to ask whether internal functional goals and objectives are really in line with competitive performance.

This becomes a basis for teams to begin challenging or reassessing the original design and planning assumptions. For example, an asset team’s supply chain and procurement strategies can be reevaluated once there is an understanding of what is really achievable in an operating area, including materials, staging and pricing. Moreover, planning around crews, rigs and other equipment has an informed basis with which to be sequenced to reduce waste.

This type of exercise is typically a very granular view around procedural assumptions. We have worked with asset teams based in the Permian Basin and the Bakken, as examples, that have taken their drilling and completions procedures and walked through each line item to ask whether the design assumption and corresponding procurement/supply chain strategies are helping the team achieve cost reductions or efficiency gains tied to externally referenced data. It should be noted that the teams also factored in HSE considerations, ensuring that those standards were not sacrificed for costs or production gains.

TOP IMAGE: Externally referenced data and key limits in each basin or play are a foundation for driving upstream value creation. BOTTOM IMAGE: Potential waste (value destruction) occurs throughout the well development value chain, hence the need for a focus on integrated planning and design to drive much more efficient execution. (Source: Capgemini)

Execution, sustainability
Once the program is designed from a competitively referenced basis, a project team can use the same external data to monitor execution and then work toward sustainability. Often, teams struggle to determine the right combination of metrics and KPIs to track and measure against. This is driven by a number of factors, including different levels of the organization focusing on different types of measures, functional metrics competing with asset or program metrics or a fundamental misalignment on what determines success in a given basin.

To determine whether the design basis is meeting competitively referenced expectations, a project team should be focused around a discrete set of “value metrics”—i.e., some variation of cost, time, production and yield (return on investment). Time is an especially important consideration as the transition among functional tradeoffs is often a leading cause of waste in that days go by without productive activity taking place as a well moves toward first production.

Using asset-focused rather than functional-focused value metrics to assess performance is one part of ensuring whether redesigned project objectives are being met. Another aspect involves regular review and updating of the comparative data to keep design and planning assumptions current. Analysis should be refreshed on a regular basis to ensure the most recent competitive view of offset operator execution.

Operational limits
As data-driven competitive models are used as a foundation for project design and execution, asset teams also should be cognizant of the design and execution limitations inherent within each basin or play. Cost and performance are impacted by four factors that have a unique profile or limit depending on where the development project is being executed. These are acreage, people, pro-
cess and technology.

The ability to drive toward competitively referenced baselines depends on how well a team acknowledges the realities of each factor in design, planning and execution. Acreage, for example, not only includes the geologic and reservoir modeling but can include existing infrastructure (or lack thereof).

People and process contemplate the experience levels and numbers of available resources in addition to maturity and optimization of relevant planning and execution processes. Finally, technology involves fi nding the right tool or enabler to help facilitate the realization of goals and objectives once goals, design and planning are all properly aligned.

The availability of Big Data to impact oilfi eld operations and project design is no longer a signifi cant challenge facing the oil and gas industry. Instead, it is how to use these data to serve as a basis for informed and integrated design, planning and project execution.

Approaching cost and performance data in a systematic, fully integrated fashion can enable organizations to navigate current realities in a challenging operating environment as well as the inevitable hurdles the industry will face in the future from planning and budget decisions made today.

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