That prospect you’re all set to drill may appear to have all the requisite attributes needed to be the real deal.
Beware.
There may be a crucial missing ingredient.
Think source rocks.
They not only must be present, they must be capable of adequately “feeding” any targeted conventional reservoir rock.
Traditionally, the approach to identify and qualify these rocks has been to use well data. But well data can be sparse or nonexistent in deep basins/frontier areas.
“There are a lot of challenges to getting well data, and the ability to use other types of data, like seismic – which you need anyway – is very important,” said AAPG member Ole J. Martinsen, vice president and head of exploration research, Technology and New Energy at Statoil Research Center in Bergen, Norway.
In Martinsen’s words: “You can extract information from the seismic that you could not do before.”
This is the basis for some innovative doings at Statoil.
A group of researchers at the company have labored for several years to develop a now-proven technology to identify source rocks and their quality from seismic data.
Dubbed “Source Rocks from Seismic” (SRfS), the patent-pending technology already has been applied successfully to certain exploration regions.
Martinsen, this year’s AAPG Foundation Roy M. Huffington International Distinguished Lecturer, emphasized the ability to predict source rock presence and quality in frontier exploration regions is highly significant in the quest to identify new exploration terrain as well as to qualify existing terrain.
The really good news for the industry is that Statoil is now willing to share some of the researchers’ insight.
“Our team is focused on using seismic data not just in a general way to see if the source rock is there,” Martinsen said, “but also to evaluate the quality and maturation to determine how well suited the source rock is to expel oil and gas to other parts of the petroleum system.”
Content and Properties
All of the technology the group is using is well known; they’re just applying it differently.
“To assess hydrocarbon source rocks, we’re using technology that would normally be used, say, to predict sandstone and fluid content in sandstone,” said Marita Gading, principal researcher at Statoil Research Center in Trondheim.
“The methodology we’ve put together allows us to do this,” she noted.
“We’ve tested it in many cases over the years, and it works on source rocks in different places of the world and different ages,” Gading said. “It seems to be valid everywhere.”
The data used don’t have to be exceptional to determine the presence of source rock, but higher quality data do provide an advantage.
“The better the data, the more detailed you can be in your predictions,” Gading said. “Then you can go all the way to say something about organic content based on seismic data – which is the ultimate in the way we see it.”
The Statoil research group has studied the relation between organic content and rock properties in order to increase their understanding of the seismic responses of hydrocarbon source rocks.
Gading noted new workflows have been established, aimed at using the information inherent in the seismic amplitudes to map and characterize source rocks.
“Source rock properties extracted from seismic data can be used directly in basin modeling and hydrocarbon generation modeling,” Gading said.
“The new seismically based workflows allow us to include source rock parameters extracted from areas without well control in the modeling,” she noted.
“In fact, source rock parameters can be extracted in all areas covered by seismic data of a certain quality.”
The seismic source rock properties can be drawn out based on established quantitative relations between organic content and rock properties.
Gading noted source rock parameters such as distribution, thickness and richness historically have been obtained from interpolating geochemical and well log data between available wells.
An Ideal Area
The research team has applied their methodology in various far-flung locales, but the Norwegian continental shelf is their largest data source. Therefore, this was an ideal area to test in order to establish the process works effectively and efficiently. The successfullycompleted project there has been written up as a case study.
“This was an independent test, a blind test, within our petroleum system that we know works,” Martinsen said. “By independent analysis, it shows seismic data itself can provide the same results as well data.
“We came up with justified results just from the seismic data,” he emphasized.
“In terms of the quality and analysis you perform, this new method is very important as there’s huge competition now to get into the best acreage in new basins,” Martinsen said.
“The technology by which you can analyze just the seismic data and get a good analysis done lets us perform a better analysis than perhaps many of the competitors at a very early stage,” he noted. “Being first requires you can make a good decision early on, ahead of the competition.”
Gading added, “This type of methodology lets us take a significant step in reducing exploration uncertainty in areas where there’s no well data and sparse seismic data.
“The established relations between organic content, rock properties and seismic responses of hydrocarbon source rocks make us able to predict presence, extent, thickness and richness of the source rock,” Gading said.
“Seismic data can thus reduce the uncertainty in some of the parameters used in basin modeling, and thereby improve ranking of basins and prospects,” she added.
Martinsen pointed out another aspect of the methodology that carries considerable weight today for a lot of folks: It’s applicable not only to conventional resources but also to the unconventional such as the now-wildlypopular – and seemingly ubiquitous – shale gas.