We here at Drillinginfo are fired-up about winter NAPE. I thought the best way to prepare myself for the expo would be by asking some of our best and brightest a few questions, and assembling their responses into a virtual panel to share with y’all!
No matter what industry you are in, accurate and timely metrics help define the practices that drive the best performers, and what changes are necessary to get or stay on top.
Oil and gas companies live and die by accurate analysis and competitive efficiency. We are constantly poring over MaxIP; 6 mo cums; oil/gas ratios; historic production numbers; geology of the rock in play; who is leasing in the area; what is expiring and when – just to find a point on a map that is undrilled with good potential to maximize the return on invested drilling dollars.
I chatted with some of our analysts, did a little research, and devised three really big questions. I hope you enjoy the responses as much as I do.
Big Question Number One: How Much is Too Much Data?
“Big data” can be confounding, unorganized and biased. How can our clients use metrics to combat these big data problems?
Mark Nibbelink (Co-Founder, Director of University Outreach):
I think that they need to thoroughly understand their database architecture and structure and make sure it’s aligned with their most important goals. Once they’ve gotten that sorted out, flagging data elements of high importance in whatever database table they have will help focus the value of their data. Metrics organized around these high value flagged data elements allow businesses to quickly snapshot both positive and negative trends.
Christopher Smith (Senior Research Analyst):
Drillinginfo builds models to explain production and predict future results. These models utilize vast amounts of data. The data ranges from the traditional to OCR and well log interpretation. We are acutely aware of problems that arise because of biases. We provide clients metrics that prove that our models perform well with out of sample data and don’t suffer from over-fitting.
Bob Black (Director, Global Analytics):
Organizing and normalizing data prior to analysis cannibalizes huge amounts of time before the value added work of drawing conclusions from the data ever begins. DI Analytics attempts to solve this problem by providing cleaned up data sets for 9 major North American shale plays. The improved data sets include permits, leasing, production, and well header data. Our analysts normalize production data by formation, consolidate operator names from various related filings, remove duplicates and counterparts from leasing data, develop true gross acreage positions for operators, and perform additional QC checks to create more accurate data sets ready for analysis. Our objective is to help our clients save time and concentrate on the work that creates the most value for them.
Kevin Thuot (Engineering Research Analyst):
The right metrics allow a company to pull the proverbial needle out of the haystack. The key is to identify what inputs have a causal relationship with the desired outputs. Those are the metrics that need to be tracked – the rest is just noise. Given the complexity of Oil & Gas industry problems, this process will often require multivariate statistical analysis, which can be done efficiently in our Transform software.
Walter Bruce (VP, Technical Business Development):
Transform Multi Variate Statistical Analysis has a Multicollinearly workflow that addresses the abundance of data. This workflow helps our customers take a multitude of data and narrow it down to relevant metrics.
Matt Menchaca (Research Analyst):
Big data isn’t a problem at all, but rather a means to a solution. In a perfect world, the data should be allowed to speak for itself. However, it’s easy to forget about the amount of power behind big data and its influential ability. There should always be checks and balances as to how the data is being prepared, served up, and where it is sourced from. Metrics allow for the integrity of the data to be analyzed in various increments, whether that be time, production volumes, etc. By slicing and dicing big data down into metrics, it allows the analyst to scrutinize over the information in smaller increments providing more clarity.
Big Question Number Two: How Can We See Into the Future?
Standard descriptive analytics merely describe the past. How can our clients use metrics to turn description into prediction to drive future results?
Batch regressions over well-chosen time series should illuminate co-dependencies in the data. Measuring real time data against those regressions should help determine whether corporate performance is diverging from historical behaviors. Early study of these divergent behaviors can lead to new regressions that can be used to predict future performance.
Folks need to understand not only the historical patterns in the data, but also the underlying relationships that caused those patterns. They need to understand causation, whether it’s a geologic deposition that is conducive to high production, or a relationship between well log data and completion techniques. For example, we provide our clients with metrics that explain the impact of well log data on production. This gives our clients a baseline understanding of what volume of production to expect from an asset based on the geologic characteristics. It’s a way to normalize for geology and estimate production. Then we provide them with metrics so they can understand what the important geologic variables are, and what mixture of those variables to look for.
Everyone knows spacing matters in field development. But what are the trends in spacing out in the field by operator within the oil, gas, or wet window of a play? DI Analytics proprietary spacing algorithm can break down this data by operator in convenient and easy to use charts that are updated as the plays mature.
Mark Twain said “History does not repeat itself, but it does rhyme.” By analyzing patterns in previous events you can make predictions about what is likely to happen in the future, even when the future scenario doesn’t have an obvious analog with the past. This gives your firm a head start when a new situation arises: you instantly see the likely course of events while others scramble to evaluate the situation based on their subjective individual experiences.
Transform Multi Variant Statistical Analysis does this. We provide our customers with a statistical answer on the prediction they are trying to make.
It’s as simple as the time old tale of what goes up must come down. Analyzing trends through metrics allows the analyst to see patterns in the data and make decisions based on their expertise of cyclical data pattern and momentum recognition in their field of discipline.
Big Question Number Three: How can Oil and Gas Companies be Certain They’re Up-to-Date?
Unconventional resource technology learning curves can be crippling to an E&P company. How can our clients be sure they are operating with the best practices of 2014 and not 2010?
First order of business is to assess the geological quality (TOC, net thickness of unconventional targets, fracability measures like Poisson’s ratio , Young’s modulus, areal extent of high quality target sections, etc. etc.) of both acquired acreage and potential lease acreage. Once this is done companies then have a base line that they can use to compare via DI Analyticis their acreage against competitors. Fanatical attention to real time competitor results will deliver maximum possible ROI to any company willing to invest in this level of monitoring.
We provide our clients with metrics to understand field development and economies of scale. Achieving economies of scale is how the most active operators make the most use of time and capital. We provide our clients metrics that take into account current well spacing, pad drilling, and monthly well rates to understand where operators are in their drilling programs. They can then understand the current state of an operator’s program, whether they are early in the exploratory phase, or achieving economies of scale with pad drilling.
One of the cool things about working for DI is providing insights that formerly took years to spread among companies in matter of days. Democratization of the oil business some like to say. Unconventional plays are experiments that evolve and change as new processes are discovered. What works best today may change with technology advancements derived from this constant experimentation. Lateral length, frac design, simulfrac methodology are just a few of the areas DI Analytics tracks to better understand the evolution of a play. By consistently monitoring the activity trends, changes can be recognized and reported to clients to create greater value for all.
Drillinginfo provides a continuous stream of the latest industry data available. By creating leading-indicator metrics that identify changes in trend from areas such as well productivity, field development practices, rig movements, etc. you will be aware of how the industry is evolving in near real-time. In trying to be ahead of the curve, there will inevitably be some false positives that need to be considered and filtered out but this approach will allow your people to evaluate current and relevant hard data, rather than just trade show talk.
Workflows in Transform Essential provide modern workflows to help our clients obtain timely answers.
The unconventional playing field is high paced. Fast action is crucial to getting out in front of the other guys. Things happen quickly throughout the entirety of the play’s development. From the scientific assessments, to the land grab, to get wells drilled, well optimization phase, efficient spacing of the wells, and eventually the hurry up and get out phase. Anybody that has been in the industry for even a little while knows that this is a cyclical game and to be successful you have to strike when it’s right.
What do you think? What else is important to measure? How do you make sure your business stays out in front of the competition? Leave a comment below.
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