PRESS RELEASE: Petryx and Getech announce database partnership

Petryx Ltd have partnered with Getech Plc, allowing customers in the Oil & Gas industry to view Petryx Database coverage alongside Getech data products. Covering every major continental mass in the world, the Petryx Database offers hinterland data essential to data-driven source-to-sink interpretations.  

Managing Director of Petryx Ltd, Lorin Davies says: “We are delighted to have partnered with Getech. This brokerage deal provides much higher visibility of Petryx datasets to Oil & Gas explorers and demonstrates Getech’s commitment to innovation. Deals like this emphasise the many ways in which the Oil & Gas industry can support innovative start-ups like ours.” 

Senior GIS Consultant, Thierry Gregorius says: “We are excited to add this valuable new data resource to the extensive product range that we offer our customers. Explorers and geoscientists will now be able to access global datasets from Petryx via Getech, including geochemistry, geo- and thermochronology, and more. With this step we are offering our customers a growing one-stop shop.” 

Petryx Ltd is an innovative digital geoscience start-up who have revolutionised data integration and acquisition processes, giving Oil & Gas explorers fast access to cleaned and standardised datasets. The Petryx Database is a multi-disciplinary geoscience dataset compiled from numerous sources with the collaboration of industry and academic partners. It offers an unrivalled view of the composition of the earth from a single unified platform. 

Source-to-sink workflows for de-risking the oil and gas reservoir

Over the last few weeks we have been spending lots of time talking to clients about some of the datasets offered by Petryx. In a few cases we have been talking to sedimentologists and geoscientists who are experienced with manipulating and interrogating datasets like ours. However, even experienced geoscientists still have questions about how to get the most out of these datasets, particularly when doing source-to-sink work. This blog explains the approach we take at Petryx when puzzling out sediment routing and prediction of reservoir quality. We outline a generalised approach, followed by some of the outputs you would expect to see from a workflow like this.

Source to sink: Detailed study of processes and products relating to clastic sediments, from their origins in the hinterland, to the sedimentary basin.

Normally, the quickest route to good interpretation is through good scientific method. In source-to-sink questions this means observing the data, be that subsurface and/or hinterland data, and formulating a question: “where and when are the good reservoir sands being deposited”, or “does my block contain good quality sand?”. Maybe we have questions about seal capacity, or maybe a group of people have a bunch of questions which we could really do with some quantifiable answers to.

The next step is to build a hypothesis based on the data we have observed. This may mean integrating drainage-basin polygons with hinterland geology and geochemical data. We can take thermochronological data and further refine our drainage basins, or adjust the expected sediment generation based upon these inputs. Paleocurrent data help us to verify where clastic systems were flowing, and further refine the drainage story. We bring in any climatic data we have and use this along with total drainage length to quantify sediment breakdown, and therefore the cleaning potential of our sands. Plate models and paleogeographic interpretations can be significant, but throughout this process it is paramount to be able to segregate the interpretative inputs from the hard data, and weight accordingly. Once we have mashed together all these data and interpretations we can make a prediction: “Given what I have observed, I think that there is lots of good quality sand going from A to B at this time”. If we have enough data, and time to work with it, we might even quantify this hypothesis with some degree of certainty (see this great book for an explanation of why you should be sceptical of predictions that people won’t put a number on).

Now the fun bit! We take some data which we have held in reserve and test our hypotheses. A great game if you are asking a service provider to give you a bespoke source-to-sink interpretation is to keep a few petrographic analyses in reserve to test some of their predictions. We sometimes get a bit upset about not getting all the data, but it is a fantastic way of testing the veracity of the predictions being made. After all, it’s better to test our hypothesis before you drill the well, rather than afterwards.

Above: One output of a hypothetical source-to-sink workflow, with mineral composition predictions from given hinterland zones. Multiple datasets can be used to give a qualitative estimate of reservoir potential, and then mixed into sediment packages. Image credit: Petryx Ltd (CC BY-SA 4.0)

Now we can start to iterate. It is OK to get it wrong as long as we find out why. Often the predictions will need to be refined and improved to reflect new data. Once we have a model which we are happy with we can take our outputs and make some quantitative statements about the subsurface. Often a report or study will stop here and not fully translate a working model into useful quantitative data, as if it is enough to say, “We have a model which explains the data well”. Let’s take that hypothetical model and share our insights with our colleagues:

  • Thermochronological data suggest up to 6 km of exhumed lithosphere over our target interval.
  • Uplift rates around our target interval suggest a significant influx of clastic material into the area around our block (15 km3) derived from hinterland A (65% certainty).
  • Siliciclastic packages in package α are likely to be composed of 55% quartz, 25% plagioclase and 20% K-feldspar.
  • Package β, whilst relatively significant in the sediment pile is likely to be largely (85%) derived from hinterland C, so could be problematic. This may mean that where it is interleaved with package α it risks washing in diagenetic fluids.
  • Package γ appears to be a distal equivalent of package α, but also contains chemical sediments. It is likely to contain up to 6% chert.
  • Package ζ is a regional seal with an expected clay content of 30%.

Finally, we want to say loud and clear what the sensitivities and testable parts of the model are. So if someone finds some data which doesn’t fit, we can iterate our model further.

  • Paleoclimatic conditions indicate high potential for sand cleaning and improved reservoir quality. Lower weathering rates and stable climatic conditions will result in lower chemical abrasion and reduced sand cleaning.
  • Little compositional data was available for the upper part of our target zone, resulting on heavy reliance on UPb data, which can be blind to mafic hinterlands.
  • We would expect little or no metamorphic minerals in package α.

To quote statistician George Box, who we think had it about right: “All models are wrong, but some are useful”. Hopefully this idealised workflow can help you get closer to that useful model and know what these datasets should be able to tell us. If you are interested in source-to-sink modelling, or want to discuss more, drop a comment below or head over to a short survey which we will be promoting in the coming weeks. We think we have some great workflows, but your opinions can really help us make them more relevant to you.

George Box. Image credit: DavidMCEddy at en.wikipedia (CC BY-SA 3.0).

By Dr Lorin Davies

A new dining experience for geoscience data consumers

This week we launched Petryx Ltd, a new company with a new vision for digital services for the Oil & Gas industry. This blog post is my introduction to the company and an opportunity for me to articulate what we are doing. It will be followed in the coming days by blog posts from my fellow directors Laura Fielding and Sam Fielding who will be giving their perspectives on what we have to offer the geoscience domain.

After a challenging few years, many Oil & Gas companies are emerging from the downturn as smaller, more responsive organisations. Whereas before a team of dozens or hundreds of explorers would have worked up prospects across the globe; now just a few skilled geoscientists must assess where opportunities lie, and work to understand the subsurface. Whilst all of this has been happening, products offered by the service industry have moved ever closer to long-term subscription models. These streamlined enterprises face many challenges, and we at Petryx are here to meet them.

In order to do the job of exploration, operators therefore have to work differently, and whilst much of this change in pace and tactics must come from within, we believe that it is the role of service companies to reflect the new face of geoscience exploration in the solutions we deliver. A trend for episodic projects have taken precedent over multi-year programmes, and now more than ever our clients must answer their technical challenges in less time. As a company, Petryx offers a portfolio of innovative new data solutions and services, which, quite simply, help our clients to get to the answers they need faster.

In a few days’ time Geoscience Director at Petryx Laura Fielding will be discussing how multidisciplinary datasets are invaluable in cracking subsurface puzzles, and this is exactly what we will be helping our clients to do with our first commercial offering. We are designing a single, connected, multidisciplinary database of geoscience data, the Petryx Database. Hosted in the cloud, this database may be mirrored by our clients directly into their private data clouds, so they can leverage the data themselves; or, if they prefer, accessed through a built-for-purpose web application which allows the data to be queried and interpreted on the fly. Our clients will be able to cross-examine their own data directly against the Petryx Database, using the web application as an interpretative tool, or upload newly acquired datasets directly into their own instance of the database.

Perhaps most importantly, the web applications and interpretative tools offered with the Petryx Database are free, and the data in our database is offered as a one-off purchase rather than on a subscription basis; so that our clients have more control and are better able to manage their budgets, focusing resources on the areas which count. We understand the needs of our clients and believe that the tools we offer and the infrastructure for serving Petryx data is our responsibility, just like a restaurant is responsible for paying the rent and providing diners with a knife and fork. As long as our customers keep buying meals, we’ll keep our side of the bargain and keep the lights on.

By Lorin Davies, Managing Director