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The AAPG/Datapages Combined Publications Database
Houston Geological Society Bulletin
Abstract
Geological
Society Bulletin
Abstract: How to Make a Map from an Outcrop
1Curtin University of Technology, Miri, Sarawak
2Nippon Oil Exploration Malaysia Ltd, Miri, Sarawak
This paper shows the process of generating a reasonable map
from a complex clastic outcrop near Miri, Sarawak,Malaysia.
Steps are: measure the outcrop, establish fault type and throw,
fault strike, fault dip; proceed with data
synthesis; make a fault
model, a
data
grid; and finally, a map.
I. Introduction
With an overwhelming, and sometimes naïve emphasis on
technology and reliance on computer
automation (“Nintendo geology,”
“Black Box monkey geology”), the basic
but absolutely essential discipline of
extracting
geological
information from
outcrops is in danger of being sidelined.
Students of petroleum geology often are
not sufficiently trained in mapping and
map generation – although these skills
are vital in the context of prospect creation. From the standpoint
of petroleum business, in which geoscientists are mainly confined
to the office environment with
geological
interpretation being
conducted on workstations, the neglect of field geology is
somewhat understandable:
outcrop
data
are difficult to
translate into numbers, and
to incorporate such numbers
on the long road from geology
to money is sometimes
an art by itself. This said,
however, it is argued that
outcrops are more than
venues for social events
and/or brain stimulators,
and some of us are still
enjoying tremendously
attending occasional field
trips. The chosen example (Fig. 1) is an extremely
tricky one. Located some
40 km SW of Miri, Sarawak,
this Coastal Road outcrop
offers excellent insight into
fault-seal and clay-gouging
dynamics.
II. From outcrop to map
Step 1 : Measuringan
outcrop: The best thing
to start with is camera,
notebook, and a GPS. This way, important landmarks, horizonfault
intersection points, etc. can be captured. The GPS data
can
be made easily decimal, and imported into an Excel spreadsheet.
It was useful to add a scale to the outcrop – in this case every
meter of the outcrop was marked along drains that intersect the
outcrop in mid-section.
Step 2: Strike and dip: Here our main tools are compass, hammer/knife, measuring tape, and notebook.
Step 3: Data
synthesis: All the
data
are
plotted onto one sheet that shows all
the
data
– GPS, horizons, horizon
thickness, faults, fault throw, relief, and
landmarks. This is shown in Fig. 2 on
next page.
Step 4: Making a fault model and a data
grid: Most outcrops are
2-dimensional, the cited example is somewhat 3-dimensional
though complex. Grids can be generated by: (1) correlating
horizons and faults between several outcrops, and using
interpolation techniques; (2) by outcrops into a well; or
(3) simply by extrapolating strike and dip
data
(as is done here)
as long as this can be justified in the context of the regional
setting and sound structural model.
Extrapolating fault data
is always tricky, but there is a statistical
relationship between fault throw and length of a given fault
[Walsh and Watterson, 1988]. A good rule of thumb is that faults
are mostly 10-times longer than their throws. Using the existing
strike and dip
data
, it is possible to create a
data
grid. Such a grid
should be regular – in this example grid nodes with 10 m distance
are chosen. Furthermore, in order to define faults, grid points first
need to be defined. In this example, points for the up- and downthrown
sides of the faults were picked every 10 m on the y axis.
Step 5: Data
export:
Data
can be exported as X, Y, Z files to any
commercial mapping package.
Step 6: Gridding and contouring
are performed. The final map is
shown in Fig. 3.
Fig.3: A simple depth map for the area NW of the outcrop, derived from the outcrop
data
.
III. Map Applications
There can be a variety of applications. In this example, the goal
was to provide data
for a clay gouging and fault rock simulation,
to compare model simulation results with measured
data
, and to
predict the clay gouging and fault rock prediction on larger faults
seen on seismic [Kessler et al., in preparation].
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