The high resolution images produced by electrical bore-hole imaging tools reveal small scale geologic features characteristic of depositional environments, and by inference, reservoir geometry.
Geologists use this stratigraphic information to define the depositional environment, helping them to pick offsets and construct better reservoir models.
Important small scale features include lateral continuity of beds, vertical changes in bed thickness, bed stacking patterns, and recognition and classification of bed disturbance patterns. Such features are resolvable only on borehole images or in core.
This article describes some techniques used in the recognition of geologic features from images and shows how these features are translated into depositional environments.
Examples show clastic depositional environment interpretation typical of sediments common in the Gulf of Mexico.
The techniques work equally well in carbonate environments.
Determining depositional environments from borehole images is similar to interpreting depositional environments from core or outcrop. The first step is to put the interval of interest into context, to look at the overall picture.
When interpreting outcrop, this means first stepping across the road to see the entire outcrop face; when interpreting core it means laying out and visualizing the entire core, then using wire line logs to interpolate beyond the interval cored.
Similarly, interpreting borehole images involves four steps. These are:
1. viewing the entire interval of interest to obtain the big picture,
2. identifying features within the interval of interest,
3. interpreting the depositional sequence, and
4. incorporating the interpretation into a geologic model.
As a prelude to the first step, it is important to use standard wire line logs to determine the lithology of the imaged interval and those on either side of it. In addition, one must estimate porosity and identify any hydrocarbon or water-bearing units from the wire line logs.
All available information regarding the regional geology should be considered during this phase of the interpretation.
When examing the entire imaged interval to determine the general depositional environment, many questions should be asked. Does the section appear massive or laminated, homogeneous or heterogeneous?
Is the section dominantly sand or shale, and in what manner does the shale occur-laminated, dispersed, or in clasts? Are the bedding contacts bounding the interval sharp or gradational?
Is there evidence of erosion or loading? Are any scour cuts present, possibly with lag deposits? Each of these characteristics is an important clue regarding the depositional environment.
In the second step, the internal structure of the interval is evaluated. Features of interest may include cross bedding, flaser bedding, or wavy bedding; shells, shell casts, burrows, fractures, nodules, or pebbles can be identified.
Disruptions of original bedding also may be seen in the form of broken bedding planes, patchy calcite cementation, and soft sediment deformation.
Next, individual bedding sequences can be identified by changes in lamination thickness or by changes in style of vertical bedding breaks (absent or gradational). The relationship of the interval of interest to the surrounding section must be described in the sequence analysis.
Finally, the sequence analysis should be compared with the depositional models and regional geology to determine a depositional environment and geologic model of the reservoir.
Three case studies are presented as a means to illustrate how the aforementioned technique can be applied to varying depositional environments.
Examples come from deepwater, near-shore, and barrier bar systems.
* Deep-water deposition. Drilling a prospect in a deep-water environment, the operator encountered a low-resistivity interval of interest, which had a very suppressed gamma ray response. Both the pay and the depositional environment needed to be evaluated in this typical low-resistivity section.
A conventional core was taken in order to identify depositional environment, but only 2 ft were recovered from an attempted 60 ft core.
Thus, an electrical borehole imaging tool was run (in this case Schlumberger's Formation MicroScanner) to complement the small core. its images, once correlated to sidewall cores, revealed thinly interbedded sand, silt, and shale, with individual sand laminations less than 10 in. thick.
Five separate laminated sequences were identified and interpreted as depositional units (Fig. 1), each consisting of a "thick" sand at the base and laminations thinning up the hole. The shales above and below the sand lacked bedding and had low resistivity (0.8 ohms).
The section was interpreted as a series of aggradational lobes on the distal portion of a deepwater, submarine slope-fan deposit. Paleo-current indicators were interpreted from the images to establish the sediment source direction for the aggrading, laterally switching slope-fan lobes.
With an understanding of the transport directions and depositional environment, a projection of reservoir geometry and lateral extent was established and an offset location selected.
* Near-shore marine deposition. A better understanding of depositional environments and subenvironments was required by the operator of a near-shore marine reservoir to help plan field development. A variety of depositional styles were differentiated by the images including:
1. massive (sands >2 ft thick with minor cross bedding and little other internal structure),
2. massive-bioturbated (sands >2 ft thick with shells and recognizable burrows)
3. laminated-bioturbated (shale laminations partially bioturbated and dispersed in sands), as in Fig. 2, and
4. laminated (interbedded, thin sands <2 ft thick and shale laminations).
Also identified were non-reservoir units such as laminated shale, carbonate cemented sand (high resistivity, often in nodular form), and deformed soft sediments (convoluted bedding, sometimes associated with slump features).
Each depositional style is associated with a separate but related near-shore environment. The massive sand, laminated sand, laminated shale, and soft sediment deformed units are associated with deltaic deposition, while the massive bioturbated and laminated bioturbated units are associated with shallow marine shoreface sands.
Estimations of reservoir connectivity were made based on the relationship between the deltaic and shallow marine sands. Identification of the less porous laminated-bioturbated sands from the images help in the selection of zones to use for water-injection of bypassed reserves.
* Barrier bar system. in a producing reservoir identified as a barrier bar system, an operator identified five rock types from conventional core.
Two bedding styles were permeable and productive, yet differentiation between productive and nonproductive zones proved very difficult using conventional log analysis (Fig. 3). To avoid the high cost of conventionally coring all wells, electrical borehole images were acquired.
Image analysis enabled the effective discrimination between silts, laminated sand-silts, heavily bioturbated sand-shales (containing a higher clay percentage and shown as dark images on Fig. 4), mildly bioturbated sand-shales (with some original depositional features undisturbed and shown as light images on Fig. 4) and lightly laminated sands (generally massive sands with minor laminations).
Based on the bedding features, depositional environment was identified as brackish to inner shelf deposition, associated with a barrier bar system. The productive, mildly bioturbated and lightly laminated zones were easily identified on the images, as well as the heavily bioturbated zones in which permeability had been destroyed.
Since permeable productive intervals were indistinguishable by conventional log analysis, the key to success was rock type identification using images.
The reservoir was a combination structural/stratigraphic trap; therefore, the identification of the depositional subenvironments on the barrier bar provided the closure necessary to prove the reservoir economics.
Electrical borehole images have proved useful in identifying a variety of depositional environments. image interpretation has been applied to:
1. determining the direction of sand thickening,
2. providing offset locations,
3. projecting a reservoir's geometry and lateral extent,
4. estimating reservoir properties for waterflood projects,
5. identifying permeable zones for production, and
6. predicting flow barriers that provide reservoir closure.
Thus, the ability to image reservoirs and interpret their geologic setting has extended beyond purely geologic applications to use in reservoir analysis.
Laura Stager Foulk received a BSE in mechanical engineering and a BA in geology from Duke University, Durham, N.C., in 1981 and an MS in geology from the Colorado School of Mines, Golden, Colo., in 1990. She has been employed with Schlumberger since 1981, working in a variety of positions such as field engineer, sales engineer, and currently as geologic interpretation/application engineer. She specializes in geologic wire line interpretation. She is a member of the AAPG, SPWLA, SEPM, SPE, and the New Orleans and Houston Geological Societies.
Foulk, Laura S. "How to learn reservoir geometry from electrical borehole images." The Oil and Gas Journal 89.18 (1991): 125+. Academic OneFile. Web. 29 Nov. 2009.
Gale Document Number:A10706412
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