Updating characterization workflows for thin beds
The Gulf of Suez Petroleum Company (GUPCO) is a joint venture between BP
and the Egyptian General Petroleum Corporation (EGPC) that focuses on oil and
gas exploration and production in Egypt. Its portfolio includes eight operating
concessions in the Gulf of Suez, with daily production of more than 78,000 bbl
of oil per day.
As part of its work on reservoirs such as Asal, Kareem, and Nubia in the
Gulf of Suez, GUPCO wanted to optimize its identification of intervals for
perforating. This required updating the company’s existing workflows for
the unconventional reservoirs and thin beds in these fields.
Identifying and evaluating thin beds using the Techlog platform
Schlumberger experts met with GUPCO to determine that a customized
solution, based on the Techlog wellbore software platform and using Techlog
Thin Beds Analysis and the Python application workflow interface (AWI), was the
most effective approach to meet these challenges.
Techlog Thin Bed Analysis is based on Thomas-Stieber modeling to
determine end points for correctly defining the response parameter values,
including saturation, for the formation components. The effect of hydrocarbon
is corrected for, and inversion curves are output.
The first step for using Techlog Thin Bed Analysis is to identify the
minerals, rocks, and fluids present in the formation. These formation
components are referred to in terms of fractional volumes. The modeled system
consists of
- wet shale, sand, formation water, and hydrocarbons in the uninvaded zone
- mud filtrate and hydrocarbons in the invaded zone.
For the sand, shale, and fluid system, the properties of clean sand,
pure shale, and the fluid must be defined. This is performed by plotting the
log data in a Thomas-Stieber crossplot. Correction to account for hydrocarbon
effects determines the porosity for the system. On the resulting plot, the
black points represent the original points and the red points are the points
obtained after the hydrocarbon correction. From this plot the clean sand and
pure shale points are graphically picked for the sand point, shale point,
structural shale point, and laminated shale point.
The Thomas-Stieber shaly sand model was originally created to resolve
the problem of laminated shaly sand sequences in older South Louisiana fields
(Thomas and Stieber, 1975). Conventional methods assume that the correlation
between the gamma ray parameter and the shale volume is a direct relationship.
The Thomas-Strieber method expects a correlation between the varying gamma ray
responses and the shale geometry because shale can exist in three different
forms in sand: dispersed, laminated, and structural. The five main assumptions
of the model are that
- Only two rock types are considered: high-porosity clean sand and low-porosity pure shale.
- Different shale types have the same mineralogy in the investigated interval.
- Shale and sand grain densities are assumed comparable. The gamma ray is equal to the number of radioactive events, the shale fraction is a function of the volume, and the radioactive events are proportional to the volume.
- Background radiation is assumed to be constant.
- The count yield does not change as rock types are intermixed.
The gamma ray and density porosity log are solved to determine the sand
fraction, sand porosity, and shale distribution, which makes the model optimal
for evaluating shaly sands that contain a mixture of mostly laminated and
dispersed shaly material. The Techlog Thin Beds Analysis module uses the
Thomas-Stieber scheme to parse a shaly sand into fractions of laminar shale and
dispersed shaly sand. The resulting fractions are used to deconvolve the
apparent average resistivity into the average resistivities of the laminar
shale and dispersed shaly sand. The porosity is then corrected using the
fraction of the shale bulk volume, and the saturations are computed for the
average dispersed shaly sand layers by using the standard Archie, Waxman-Smits,
and normalized Waxman-Smits-Juhasz methods.
The first stages of Techlog Thin Beds Analysis require using the total
porosity system. This model has been validated in turbiditic, deltaic, and
aeolian depositional environments. The advantage of this method is that it
makes it possible to distinguish zones in a highly laminated sand where the
shale resistivity dominates the apparent resistivity, which biases conventional
resistivity-based analysis to obscure zones that might produce hydrocarbon.
