Blocking well log curve data is a method of upscaling high resolution petrophysical data (relative to conventional seismic acquisition data) to a lower resolution by intelligently blocking zones of geologic packages. Each geologic package is expected have similar properties and the objective is to remove small variations within the package and replace with a single value producing a "blocked" curve.
For this example, a well from the Teapot open source dataset has been used. Information from the LAS file is given below.
Mnemonic Unit Value Description
-------- ---- ----- -----------
STRT F 4332.0 START DEPTH
STOP F 449.0 STOP DEPTH
STEP F -1.0 STEP
NULL -999.25 NULL VALUE
COMP DEPARTMENT OF ENERGY COMPANY
WELL 48X-28 WELL
FLD NAVAL PETROLEUM RESERVE #3 FIELD
LOC 490' FSL, 2449' FWL LOCATION
CNTY NATRONA COUNTY
STAT WYOMING STATE
CTRY COUNTRY
API 49-025-23195 API NUMBER
UWI UNIQUE WELL ID
DATE 15-Mar-2004 LOG DATE {DD-MMM-YYYY}
SRVC Schlumberger SERVICE COMPANY
LATI DEG LATITUDE
LONG DEG LONGITUDE
GDAT GeoDetic Datum
SECT 28 Section
RANG 78W Range
TOWN 39N Township
Mnemonic Unit Value Description
-------- ---- ----- -----------
RUN 1 RUN NUMBER
PDAT GROUND LEVEL Permanent Datum
EPD:1 F 5105.0 Elevation of Permanent Datum above Mean Sea Level
EPD:2 F 5105.0 Elevation of tool zero above Mean Sea Level
LMF KELLY BUSHING Logging Measured From (Name of Logging Elevation Reference)
APD Elevation of Depth Reference (LMF) above Permanent Datum
These examples use the Gamma Ray curve, but any curve could be used.
The simplest method of log blocking is to use a constant thickness. This method replaces each window of constant thickness, or constant number of samples in this case, with the median value in that window.
A more robust approach is to use the analysis of variance statistical method to determine the index at which two zones within a region are statistically different. Al-Adani (2012) provides a basic summary:
1. Select a zone break point to divide into two new zones. Each zone should include at least two sample data.
2. Calculate the *mean variance within zones (MVWZ)* and *mean variance among zones (MVAZ)*
3. Compute the *ratio of variances (R)*
The mean variance within zones is defined as:
The mean variance among zones is defined as:
To determine the breakpoint, all possible "splits" or division into two zones are tested. The breakpoint is the index with the largest ratio of variances, defined as:
HERE IS SOMETHING DIFFERENT In reading through the procedure, particularly the first step Select a zone break point to divide into two new zones, one may postulate the best data structure for this is a binary tree. The implementation here recursively builds a binary tree (using the third party library and open source project binarytree) where the leaf nodes are the breakpoints in order from left to right. This is illustrated in the notebook example_tree.ipynb.
Once all the breakpoints are determined, each zone can be "blocked" using the median or mean value within the zone. The result is a "blocked" or "zoned" well curve. An example is given in the notebook example_anova.ipynb
- Al-Adani, Nabil, 2012, Data Blocking or Zoning: Well-Log-Data Application: Journal of Canadian Petroleum Technology.
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