Drilling & Completions / Transfer

Extracting and Utilizing Valuable Rock Property Data from Drill Cuttings

Why the Fuss About Rock?

The relentless improvement in computing speed and power, furthered by the advent of essentially unlimited cloud-based computing, has allowed the upstream oil and gas industry to construct and run complex, multi-disciplinary simulations. We can now simulate entire fields – if not basins – at high resolution, incorporating multiple wells within highly heterogeneous structural and lithological environments. Computing power is no longer the limitation; we’re constrained by our input data.

Massive volumes of three-dimensional seismic data and petrophysical logs can be interpreted and correlated to produce detailed geological models. However, populating those models with representative mineralogical, geomechanical, and flow properties relies on interpolation between infrequent physical measurements and well logs. This data scarcity introduces significant uncertainty into the model, making it harder to history match with actual well performance and reducing predictive usefulness.

Physical measurements – to which wireline logs are calibrated and from which critical correlation coefficients are determined – are typically made on samples taken from whole cores. Some measurements can be performed on side wall cores collected after the well has been drilled using a wireline tool. However, intact side wall cores suitable for making rock property measurements aren’t always retrieved, and the sampling depth is relatively inaccurate compared to the precise drilling of test plugs from a whole core at surface.

The drilling, retrieval, and analysis of a full core adds significantly to well construction time and can cost anywhere from $0.5 to $2.0 million. In today’s cash-constrained world, that’s a tough ask. Core analysis has become faster and cheaper, but cores are still only collected from less than one percent of wells drilled. This produces a very sparse data set of rock property measurements across an area of interest.

Overlooked Rock Samples

Drill cuttings are an often-overlooked source of high-density rock samples. Although most wells are mud logged for operational geology purposes, such as picking casing points or landing zones, the cuttings samples are frequently discarded without performing any further analysis.

Geochemical analysis at the wellsite is sometimes used to assist with directional drilling. However, detailed characterization typically requires transporting the samples to a central laboratory where they can be properly inspected, separated from extraneous material, and processed to ensure a consistent and representative measurement.

At Premier, we encourage our clients to secure and archive cuttings samples from every well they drill. Even if the cuttings won’t be analyzed right away, they represent a rich, dense sample set from which lateral heterogeneity can be measured and used to fill in the gaps between wells where whole core has been cut and evaluated.

Figure 1: The images above show how rock properties can be collected, analyzed, and visualized from cuttings.

Rapid, high-resolution XRF measurements and state-of-the-art x-ray diffraction (XRD) can be used to match mineralogical signatures from cuttings to chemofacies observed in offset cores.

Information from cuttings samples expedited from the wellsite for fast-turnaround analysis can be used to optimize completion and stimulation of the well being drilled. For example, geomechanical properties correlated with the chemofacies identified along a horizontal well can be used to adjust stimulation stage boundaries. The objective is for every fracture initiation point within a stage to encounter rock with similar geomechanical characteristics, increasing the probability of successful fracture initiation at each point.

On a slower timeline, a more detailed suite of laboratory measurements can be completed, providing information about porosity, pore structure, permeability, thermal maturity, and hydrocarbon content.

The Cuttings Motherlode

In late 2017, Premier Oilfield Group acquired the Midland International Sample Library – now renamed the Premier Sample Library (PSL), which houses an incredible collection of drill cuttings and core samples dating back to the 1940s. The compelling story of how we saved it from imminent demise is the subject of another article. Suffice to say the premises needed some TLC, but the collection itself is in remarkable condition.

Figure 2: Original sample library at the time it was acquired by Premier.

The library is home to over fifty million samples from an estimated two hundred thousand wells – most of them onshore the United States, and many within areas of contemporary interest like the Permian Basin. It gives us the ability to produce high-density rock property datasets that can be used to reduce the uncertainty in all manner of subsurface models and simulations.

New samples are donated to the library each week, many of them from horizontal wells. This provides invaluable insight into lateral facies changes and reservoir heterogeneity. Instead of relying only on the sparse core measurements discussed earlier, our 3D reservoir models can now be populated with superior geostatistical distributions conditioned with data from hundreds of sets of horizontal well cuttings. In an ideal world, cuttings samples from every new well drilled would be contributed to the collection, preserving that information for future generations of explorers and developers.

We have already helped many clients study previously overlooked intervals by reaching back in time to test samples from wells passing through to historically more prolific horizons. Thanks to their predecessors’ rock squirreling habits, these clients have access to an otherwise unobtainable set of data.

Our processing team works around the clock to prepare and characterize library samples, adding more than 2,000 consistently generated data points to our database each day. Since it would take years to work through the entire collection, we have prioritized wells that will give us broad data coverage across basins of greatest industry interest. Over time, guided by our clients’ data needs, we will expand that coverage and create even higher-density data sets.

Share and Apply the Data

At Premier Oilfield Group, we believe that generating and sharing rock and fluid data is the key to making more efficient and more effective field development decisions. The Premier Sample Library is a prime example of that belief in action.

Following an intense program of scanning, digitization, well identification, and location, we are now able to produce a searchable, GIS-based index for a large part of the collection. Many of the remaining boxes are hand-labeled with long-since-acquired operating companies and non-unique well names but forensic work will continue in an attempt to match them with API-recognized locations.

We are excited to have just launched the first version of our datastak™ online platform. This will finally make the PSL collection visible to everyone. Visitors can see detailed, depth-based information on sample availability and any measurements that have already been performed. Subscribers gain access to data purchase and manipulation tools and, as the platform develops, we will add click-through functionality to display underlying test results and images.

Subscriptions for datastak™ cater to everyone from individual geologists to multi-national corporations. We want the data that’s generated to be as widely available and applicable as possible.

Rock properties available through datastak™ provide insights during several critical workflows. These often require integrating rock properties with other data sets, such as offset well information, pressure pumping data, and historical production. Many of the data types generated through cuttings analysis can already be brought into Petro.ai® and made readily available for engineers and geologists. This provides a rich data set, ready for analytics.

For example, Petro.ai® can be used to build machine learning models that tease apart the effects of completions design and reservoir quality on well performance. Premier and Ruths.ai continue working collaboratively to identify additional data types and engineering workflows that will help ground advanced analytics with sound geologic properties.

Armed with a consistent, comprehensive set of rock property data, developers will be in a position to separate spurious correlation from important, geology-driven causality when seeking to understand what drives superior well performance in their area of interest. Whether that work is being carried out entirely by humans or with the assistance of data science algorithms, bringing in this additional information will enable more effective field development and increase economic hydrocarbon recovery.

For further information on Premier Oilfield Group, please visit www.pofg.com.

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