Narrated Slideshow: neoSCAN Keeps Explorers Exploring

NS-neoSCAN

Low oil prices and tight budgets don’t mean you need to stop exploring. NEOS recently announced the launch of its second generation neoSCAN™ solution (click here to read the press release), an offering designed to keep explorers exploring even in a $50 oil world.

Requiring no new data acquisition, the neoSCAN helps you get the most out of your legacy G&G investments by integrating existing data you already have with additional multi-physics datasets that can be quickly and inexpensively obtained from a variety of sources.

The datasets that are integrated and interpreted on a neoSCAN project include:

[pullquote align=”left” textalign=”center” width=”100%”]In < 100 days and for < 50 cents per acre, neoSCANs deliver the interpretive products you need to keep exploring, including 3-D subsurface models, maps of faults and intrusives, and maps of basement topography and composition.[/pullquote]

Perhaps best of all, predictive analytics methods are applied on all neoSCAN projects, providing rich insights into the G&G attribute suites that are associated with nearby fields or known sweet spots, insights that can be used to highgrade acreage in underexplored areas.

The interpretive products generated on a neoSCAN typically include:

  • Assessments of basin-scale geologic trends
  • Maps of basin architecture and regional structure
  • Maps of key lineaments, regional fault systems, and intrusives
  • 2-D and 3-D structural and stratigraphic models
  • Maps of basement topography, faulting and composition, and the role these geologic features played in field location and type (gas vs. oil)
  • Assessments of relative acreage prospectivity derived using predictive analytics.

[pullquote align=”left” textalign=”center” width=”100%”]A neoSCAN project can be executed either onshore or offshore and for either conventional or unconventional shale plays.

Typical areas of investigation range from 2,000 to 6,000 square miles (~5,000 – 15,000 square-kilometers), although some projects have been scoped and delivered at the country scale.[/pullquote]

Even in a $50 oil price world, the neoSCAN allows geoscientists to continue assessing the hydrocarbon prospectivity of large areas such that, when opportunities for acreage or corporate acquisition present themselves, or the commodity cycle turns to the upside, they’ll have the insights they need to deliver.

To learn more about the neoSCAN, click here or on the image above to watch the narrated slideshow. Or read more about the neoSCAN on the NEOS website.

neoSCAN in Action: Athabasca Uranium Deposits, Canada

Claim holdings in the Athabasca Basin, Saskatchewan, Canada
Claim holdings in the Athabasca Basin, Saskatchewan, Canada

The Athabasca Basin is a 100,000 km2 region of northern Saskatchewan, Canada that is home to the world’s leading source of high-grade uranium. The basin is filled with sandstone sediment varying from 100 to 1,000 metres in depth. The uranium ore is mostly found at the base of this sandstone, at the point where it meets the basement.

NEOS will be presenting the results of a recent neoSCAN study covering the uranium deposits of the Athabasca Basin at the Prospectors & Developers Association of Canada (PDAC) annual conference next week in Toronto.  The PDAC exists to promote a responsible, vibrant and sustainable Canadian mineral exploration and development sector and is perhaps best known for its annual convention, which last year attracted 25,122 attendees from 103 countries.

NEOS was invited to present at PDAC 2015 by Geosoft® Inc., a leading provider of integrated geoscience software for mapping and modeling the Earth’s subsurface.  In the PDAC presentation, NEOS plans to share techniques it has been using in oil & gas exploration – focusing especially on basement mapping and predictive analytics methods – with geoscientists involved in minerals exploration and development.

To demonstrate the application of these techniques in the mining sector, NEOS undertook a neoSCAN study of a portion of the Athabasca Basin for which it integrated and simultaneously interpreted several existing geological and geophysical datasets to map key regional geologic features in a 17,000 km2 area of investigation.

The legacy geo-datasets that NEOS analyzed included gravity, magnetic, electromagnetic and radiometric as well as sub-sets of available geologic information.  Intermediate interpretive products including fault density and basement burial-depth maps were also generated and subsequently analyzed using predictive analytics techniques.

Dr. Craig Beasley, Chief Science Officer for NEOS, commented,

[pullquote align=”center” textalign=”center” width=”100%”]“In under a month, we were able to identify some of the key G&G attributes that correspond to the locations of Athabasca’s known uranium deposits. I think this demonstrates that an analysis of existing multi-physics data using advanced quantitative interpretation techniques can be a useful method for de-risking exploration acreage and improving discovery success, whether we are talking about the search for minerals or for oil & gas.”[/pullquote]

To learn more about the neoSCAN as applied to acreage highgrading for uranium in Athabasca, click here (or on the image below) to watch the narrated slideshow.

AthabascaCover

NEOS’s domain expert on predictive analytics, Emmanuel (‘Manu’) Schnetzler, will be presenting the results of this Athabasca neoSCAN study, entitled, ‘Predictive Analytics of Multi-Disciplinary Data for Basin and Basement Studies,’ during the PDAC conference on Monday March 2nd at 10AM EST in Room 716 (Adopting Tools & Techniques from the Oil Patch session) at the Metro Toronto Convention Centre.

The neoSCAN – Keeps Explorers Exploring in a $50 Oil World

[pullquote align=”left|center|right” textalign=”left|center|right” width=”40%”]With these prices, it will be difficult to justify a new acquisition program. We’ve got to make sense of all the data we already have![/pullquote]

This is an actual and recent quote from a Global Basin Studies manager at one of Europe’s most successful oil & gas exploration companies. And I’m sure he’s not the only one with this opinion.

In fact, during the last oil price bust (in 2008-09) some of us heard similar things at our former employer – a leading geophysical equipment, services and data library company.

At some level, who could disagree?  While the world is awash in oil at present, the oil & gas industry is awash in geo-data, and has been for some time.

But just having data isn’t enough. One needs to make sense of what all that data is saying.

Enter the neoSCAN™, a low-cost, high-value data integration and interpretation offering from NEOS designed to help you make sense of – and maximize the value of your legacy investments in – all your geo-data.

Said another way, NO NEW ACQUISITION REQUIRED!

neoSCANBenefits

The neoSCAN brings together legacy seismic, well, gravity, magnetic, remote sensing and many other multi-physics measurements in order to help you generate an integrated, 3-D, basement-to-surface understanding of large areas quickly and cost effectively.

In 100 days and for under $1 million (for areas of investigation up to 10,000 sqkm | 4000 sqmi), the neoSCAN will deliver many of the interpretive products you need to keep exploring:

  • 2-D structural & stratigraphic cross-sections
  • Regional 3-D subsurface models
  • Regional isopach & burial depth maps
  • Maps of basement topography and composition
  • Depth-to-basement maps
  • Basement-to-surface maps of lineaments & major faults
  • Regional resistivity models
  • Classified maps of multi-spectral data (lithology, IHIs)
  • Maps of relative acreage prospectivity
  • Identification of G&G attributes driving (un)favorable exploration potential.

By applying our proprietary predictive analytics methods to quantitatively assess all of this geo-data, we’ll help you highgrade acreage throughout your entire area of investigation.  Just like we did for this cost-conscious Global Basin Studies manager in his prospects onshore and offshore West Africa.  And just like we did for others in West Texas, the Mid-Continent, Oman, Jordan and other mature and frontier hydrocarbon provinces around the world.

[pullquote align=”left|center|right” textalign=”left|center|right” width=”100%”]Low prices and tight budgets don’t mean you need to stop exploring. The neoSCAN will help you get the most out of your legacy G&G investments by integrating existing data you already have in-house with additional multi-physics datasets that can be quickly and inexpensively obtained from a variety of sources.[/pullquote]

So when things return to normal – or opportunities to capture assets from distressed players present themselves – you’ll be prepared with the insights needed to deliver.

Low prices. More insights. Keep on exploring with the neoSCAN.  To learn more, watch the narrated slideshow.

SEG Presentation: Case Study – Appalachian Basin

Case study_Appalachian Basin_SEG 2014_v2_10-24The last presentation from our SEG Presentation Series is the narrated presentation: Case Study – Appalachian Basin.

Take a few minutes to learn more about this program and how we used predictive analytics to depict the most (and least) prospective areas for leasing, drilling or further G&G study in the Marcellus shale, resulting in improved exploration cash flows.

Click here or on the slide image to view the presentation.

SEG Presentation: Predictive Analytics in Exploration

DSC01702The next presentation from our SEG Presentation Series is the narrated presentation: Predictive Analytics in Exploration.

Sit back and relax, while you listen and discover how geostatisitical predictive analytic methods are successfully leveraged for superior understanding of subsurface conditions and reservoir performance as well as to support deeply integrated, highly-informed project decision-making.

Click here or on the image above to view the presentation.

NEOS Tech Series: Predictive Analytics to Support Big Decisions

Geostatistical Predictive Analytics is a crucial part of the Multi-Measurement Interpretation (MMI) methodology. The term Predictive Analytics itself is a bit of a buzz term that can be used to describe any approach to data mining to predict trends or behaviors in the effort to identify risks and opportunities.

Among the various approaches to Geostatistical Predictive Analytics are Static Uncertainty Analysis and Correlative Predictive Analytics (CPA) – each deals with a multitude of input data where a toolkit of techniques is applied to produce useful outputs, such as sweet spot maps. At NEOS, we execute these two approaches to mathematically and objectively identify the most relevant geo-measurements that align with the most productive wells or with the location of known wells. In essence, it is this data that provides that key additional insight to the customer, allowing them to make the all-important big decisions.

But what specifically are Static Uncertainty Analysis and CPA? How do they differ and when does NEOS apply each? We’ll start with Uncertainty – stay tuned to Sweet Spots blog for more on CPA.

Quantitative Risk Analysis

We are each faced with uncertainty every day; by definition this means we encounter more than one possibility in many different situations. Who will win the World Cup? While uncertainty is everywhere, only those states of uncertainty where there are personal stakes involved include risk (such as a potential loss or catastrophe). Should I buy this stock? It is this risk that drives individual need to make an educated decision.

To better understand this concept, consider weather. Weather is uncertain. Each day quantitative risk analyses (aka – weather forecasts) are generated for you to make various decisions about how to approach your day. Quantitative risk analysis can be performed a couple of different ways. One source might predict the forecasted temperature for September 15th in Pittsburgh deterministically (with single-point estimates) while another might do so probabilistically (with a range of possible values). A deterministic outcome would give a single value, say 63F with no rain. A probabilistic outcome would give a distribution of temperatures, with a bell curve peaking at 63F and percentage probability (30%) of rain.

We know that the deterministic answer (no rain) is possible, but we understand that there is uncertainty in the forecast and we are accustomed to hearing terms such as “chance of rain” or “probability of precipitation”. While a deterministic answer is useful, a probabilistic answer is necessary to make an informed decision.

In this example, there is uncertainty in the estimate, but unless we have a personal stake and decision to make (we will be in Pittsburgh on September 15th and we need to decide whether to bring a raincoat) that uncertainty does not translate into a risk.

Geostatistical Uncertainty

Uncertainty exists in oil & gas exploration, where there are high stakes and [often] high risk, typically as a result of limited available data and information. This perfect storm scenario makes the uncertainty analysis necessary for operators to make those all too important decisions of where to explore, lease or drill.

“When data is sparse and uncertainty if high, that’s the best time to model things probabilistically.” Patrick Leach

NEOS takes both a deterministic and probabilistic approach to decision making in the presence of uncertainty, beginning with a single common base case conceptual model and ultimately creating a uncertainty assessment that addresses questions, intended for integrated team discussion, like what is the total volume of oil, what are the areas of interest for oil and what may contribute to uncertainty in the area.

As an example, the Oil in Place (STOIIP) model below defines how oil volume is calculated for a formation. While by no means the only important consideration, in place volume estimates and uncertainty models are the foundation of many decisions one has to make in the life of an oil or gas field. For each input parameter in STOIIP, we define an uncertainty model through a set of probability distributions or more complex spatial uncertainty models.  Through Monte Carlo Simulation, the input uncertainties are combined into a model of uncertainty for STOIIP.

Oil in Place Model
Oil in Place Model

Global uncertainty in STOIIP can be represented by its distribution, typically normalized per unit area (square miles in this case).

Global uncertainty in STOIIP (MMbbl/square mile)Local uncertainty can be represented through different maps, such as standard deviation maps, P10/P50/P90 maps or probability of being above a given cutoff.
Global uncertainty in STOIIP (MMbbl/square mile)

Local uncertainty can be represented through different maps, such as standard deviation maps, P10/P50/P90 maps or probability of being above a given cutoff.

Probability for STOIIP being above 50 MMbbl/square mile
Probability for STOIIP being above 50 MMbbl/square mile

Finally, it can be useful to look at the contributions of the different sources of uncertainty with tornado charts.

Contributions of the different sources of uncertainty to the global uncertaintyContributions of the different sources of uncertainty to the global uncertainty
Contributions of the different sources of uncertainty to the global uncertainty

As with our weather example, while a deterministic approach (STOIIP) is useful, including a probabilistic approach is necessary to make an informed decision, which can range from leasing an area, selling it, drilling exploration wells, designing data acquisition surveys, to development strategies.

This means that a good understanding of our clients’ objectives and in particular the decisions they are facing is crucial in order for NEOS to deliver information that helps make those all-too-important informed decisions.

If you would like to learn more about the NEOS approach the Predictive Analytics read this White Paper or see related Sweet Spots blog posts.