Resolving thin stringer sands

Novel processing techniques help one operator overcoming obstacles

related to thin, sub-seismic features in the shallow Gulf of Mexico.

Article By Emely Shay, SMT

Published Jul 2, 2008

In the 1900s it wasn’t uncommon to search for oil tucked beneath

structurally simple anitclinal traps. However, geoscientists have

to work much harder today to discover economic reservoirs.

Searching for hard-to-find stratigraphic traps is common as we

reexamine mature plays to uncover missed hydrocarbons. These

days, simply relying on the full-stack amplitude response as a

direct hydrocarbon indicator isn’t enough; typically, advanced

reservoir characterization techniques and seismic attribute

analyses (pre- and post-stack) are needed to evaluate a reservoir

properly.

Merit Energy Company, a large independent oil and gas company

based in Dallas, exploits shallow offshore fields in the Gulf of

Mexico and explains the processes used to effectively resolve their

datasets. “We try to use the latest technology to best image our reservoirs,” said Staffan Van Dyke,

a geophysicist with Merit Energy.

Thinner beds off the Gulf of Mexico

Each Merit Energy project typically includes three to 300 wells. In addition, the company has

loaded data for thousands of wells offshore. It also has 200 to 300 GB of full-stack 3-D seismic

(prior to running attributes). The organization exploits the entire shallow offshore Gulf of Mexico.

Some of the environments of deposition it encounters include deltas, near-shore slope deposits,

thin-bed sands, and salt-associated features. Merit mainly exploits clastic reservoirs associated

with shallow Gulf of Mexico deposits which range from 4,000 to 12,000 ft (1,220 to 3,660 m) in

depth.

Though most datasets contain higher frequencies near the surface, all frequencies attenuate as the

wave front propagates deeper into the subsurface. Many of Merit’s reservoirs lie in depths where

they are primarily imaged by frequencies as low as 10 to 20 Hz. This means that beds that are 15

Example of Flex Gridding and its

parameters. The algorithm for this

feature tends to result in tighter,

smoother grids than most others

available.

to 20 ft (4.5 to 6 m) thick are sub-seismic in nature (i.e., they cannot be resolved by the seismic

wavelet and are considered to be below the tuning thickness). These are the type of thin stringer

sands that Merit encounters on a daily basis. Given the low frequency content of these datasets,

advanced attribute analyses techniques are required to properly evaluate these deposits.

Van Dyke explained how Merit uses other processes to supplement its exploitation, uncovering

data that traditionally goes undetected. These processes include pre- and post-stack attribute

analyses, amplitude vs. offset (AVO) analysis, seismic inversion, spectral decomposition, and

advanced mapping techniques.

Post-stack attribute analysis

At times Merit reprocesses the data with outside vendors such as Geotrace to increase the signal-

to-noise ratio and to enhance the higher frequencies in the post-stack dataset. Geotrace’s

Bandwidth Extension (BE) technique is one that Merit uses extensively. This algorithm increases

the frequency content significantly without damaging the amplitude response. The newly

enhanced dataset becomes the basis for all subsequent interpretations and attribute analyses.

Van Dyke said, “Post processing techniques such as Geotrace’s Bandwidth Extension have

enabled us to greatly increase the signal-to-noise ratio by getting a higher frequency content out

of the initial full-stack dataset. Then we use KINGDOM-RSA to extend the frequency content even

further (via spectral decomposition) to focus in on the higher frequencies. This helps in

determining the three-dimensional continuity and lateral distribution of the deposits.”

Spectral decomposition and seismic inversion with other attributes offered in SMT’s KINGDOM

Rock Solid Attributes (RSA) and KINGDOM TracePak are run on this dataset as well. These

attributes help to reveal subtle features in the dataset that previously were impossible to image.

AVO

In addition to post-stack attribute analyses, Merit uses KINGDOM to gauge AVO response

quickly. The KINGDOM AVOPAK component images gathers on the fly. Van Dyke describes the

tool as easy for loading data and creating angle and corridor stacks quickly. “Utilizing AVOPAK

gives you a snapshot of AVO potential,” he said.

“Through cross-plotting, you can quickly determine the background AVO trend and gauge the

potential of an environment with the click of your mouse. After calibrating the data, commercial

volumes of gas can typically be distinguished from fizz gas [non-commercial accumulations of

gas].”

Spectral decomposition

During the course of attribute analyses and AVO analysis, Merit also uses spectral decomposition

(spec decomp), which helps resolve the data by breaking it into its component frequencies. This

helps isolate the interval of interest while reducing noise.

“There are huge benefits to using spec decomp,” Van Dyke explained. “After determining the

tuning thickness for your interval of interest, the most optimal frequency subset can then be

selected to properly map and evaluate that interval.” Van Dyke uses a non-standard or octave

scale to avoid potential harmonics (seeing the same information at multiples of its base

frequency). After producing the frequency subset, he uses Automatic Gain Control (AGC) with a

0.25 to 1.0 second window to reduce amplitude ringing. Almost immediately, the continuity of

reflectors begins to stand out. As a result, the ringing and noise in the background that tend to

distort the full-stack image disappears making it is easier to map events and horizons. A history of

successes with this technique has led Van Dyke to use spectral decomposition on nearly all of his

projects.

KINGDOM-RSA contains numerous algorithms that allow for detailed manipulations of bedding

planes. “I use the Instantaneous Dip algorithm on maps to look for faults and fine-tune the fault

grid I’ve interpreted,” he said. “[KINGDOM] has the capability to do lots of attribute analyses,

enabling you to get the most out of your dataset.”

By using spectral decomposition, Van Dyke extracts the frequency content even further, and at

times he is able to completely resolve these smaller beds.

Van Dyke has a spectral decomposition technique that he finds to be particularly effective. After

mapping the event in one of the frequency subsets, the Extract Datatype feature is shown in

KINGDOM and used on all other frequency subsets. Responses within each subset frequency, e.g.,

10.0 Hz, 30.7 Hz, and 61.9 Hz, can be observed. He explained, “Each one will tell you something

different about the reservoir. You see things that you could never see in the full-stack seismic.

That is why spectral decomposition is so great. When you are done, you can run all of the RSA

attributes to explore the reservoir. I typically use Instantaneous Phase and Instantaneous

Frequency, but I always check the others to see if there is any geologic information there.”

Flex Grid and Grid Editor

When mapping a horizon, the goal is to have it match formation tops. Regular gridding

algorithms are not usually robust enough to help tie to these tops.

“SMT’s Flex Grid makes smoother, tighter grids while working faster than other gridding

algorithms,” said Van Dyke. “By quickly seeing a preview, you can tune parameters before the grid

is made, which saves us lots of time.” Grid Editor enables the user to manipulate the grid in a

push-and-pull manner with the mouse and instantly see adjustments to the grid and contour lines

without having to reset the lines point-by-point, an effective and time-saving technique.

Conclusions

In an effort to re-examine mature plays and discover undetected data, Merit has been successful

at using advanced reservoir characterization techniques and seismic attribute analyses to see

beyond the full-stack amplitude results. Merit has been very successful at exploiting these mature

fields and credits its success, in part, to its adoption of cutting-edge tools to help it reach its goals.