| AutoDip
and TrendSetter services automate dip and dip trend
analysis of electrical micro-imaging (EMI™) borehole
data. These services save time and provide high-quality
data that can help spot "hidden features" in sedimentary
beds and laminates. |
| AutoDip
automates high-resolution dip detection, a vast
improvement on tedious manual dip picking. Unlike
traditional dip computation methods, AutoDip does not
simply correlate raw resistivity data. This method
operates independently of often inappropriate
correlation parameters, such as correlation length, step
length, and search angle. |
| TrendSetter augments AutoDip
functionality by taking dip data and automatically
sorting it into categories of: |
- Constant dip with depth
- Increasing dip with depth
- Decreasing dip with depth
|
| TrendSetter helps characterize geologic
features based on dip trends. AutoDip and Trendsetter
provide a continuous plot with a break out of dip trends
and constant dips. These dips and trends can be easily
recognized and incorporated into a geological model. |
| AutoDip
and TrendSetter differentiates themselves by selecting
bedding features more quickly and consistently than hand
picking. This provides more time to view the results and
interpret the data. |
|
| » AutoDip |
| AutoDip
uses data from all 150 resistivity buttons— not just 4,
6, or 8—to more accurately determine dips. By using more
data, more accurate dip readings are possible. |
|
| AutoDip
translates the human visual experience of event
correlation into an equation that quantifies visual
recognition to obtain the optimal dip. The
selfoptimizing algorithmic process1 operates without the
need to adjust correlation parameters, which can
introduce bias into dips or even hide dips when using
traditional methods. |
|
| AutoDip
works equally well in simple bedding or in more complex
bedding environments. |
|
| » AutoDip Features |
| AutoDip
contains the following features: |
- Uses all 150 buttons to compute dips
- Uses quality curves to optimize dip selection
- Removes user bias in selecting dips
|
| » AutoDip Benefits |
| AutoDip
offers the following benefits: |
- High quality
- Greater data confidence
- Improved dip statistics
- Reduced time to pick dips
- Production of five dip qualities
- Consistent picks independent of interpreter
bias
- Output curves that indicate degree of
laminations
- Output curves that indicate degree of bed
contrast
- Independence from search angle, correlation
length, and step length
|
|
|
|
| Slumping and soft sediment deformation
are evident in this section of log. The AutoDip program
does a good job of capturing the changing dips. |
|
| » TrendSetter |
| The
AutoDip program can generate many dips. The number of
dips is partially determined by dip quality filters.
During the analysis process, it is prudent to look for
patterns to help recognize trends that can impact
mapping, offset wells, and describe depositional
environments and structural changes. TrendSetter
automatically separates dips into constant, increasing,
and decreasing categories, making it easier to visualize
changes and trends. |
|
| TrendSetter separates the dips from
stratigraphic events such as current bedding, slumps and
drapes, from the more constant structural dips, which
allows better estimates of local structural dip. |
| » TrendSetter Features |
| TrendSetter contains the following
features: |
- Automates the selection of dip trends
- Provides quality curves used to control grade of trend
- Removes scatter from structural dip
trend
|
| » TrendSetter Benefits |
| TrendSetter offers the following
benefits: |
- Identification of dip trends
- Helps remove random scatter and stratigraphic dips from structural dip analysis
- Identification of other stratigraphic or
structural events when used with other geologic
data
- A user interface that provides flexibility and
quality control
|
| 1Shin-Ju Ye, et al., Automatic
High Resolution Sedimentary Dip Detection on Borehole
Imagery (SPWLA 38th Annual Logging Symposium,
1997) |
|
|
| Inputs |
EMI data set |
| Outputs |
Computed dips and dip
trends |
|
|
