Licensing options for this format begin with FME Desktop Professional Edition.
The Well Logging Ascii Standard Reader allows FME to read WLAS files. FME supports WLAS versions 2.0 and 3.0
Overview
The data in a WLAS file is intended for the purposes of organizing digital log curve information. Log curve information contains information about formation parameters versus depth, so interpreters can identify characteristics and types of material (for example, soil, mineral, petro) found at a certain depth. A variety of software (and possibly hardware) solutions exist to create WLAS files. However, the format is specified by the Canadian Well Logging Society.
Each file contains 1 or more sections, where each section has a header as the first line, followed by an arbitrary amount of data lines. A header is denoted by having a ~ as the first character on that line. There are 4 types of sections/feature types:
- Parameter Data
- Column Definition
- Column Data
- Other
Reader Overview
FME considers a single WLAS file to be a dataset and each section to be a separate feature type .
The reader will produce one feature per data line in Parameter Data sections and Column Definition sections. Those features will always have these attributes:
- mnemonic
- unit
- value
- description
If format and association is present on the line, the feature will also have these two attributes:
- format
- association
Since the structure for a parameter data/column definition section is well known, the schema feature is mostly static in the sense that it will always have the attributes mnemonic, unit, value and description. However, the type of those attributes is determined by looking all features of that feature type/section. For example, if all features have an int in the value attribute, then the value attribute will have type int. However, if some features have an int in the value attribute and some had text in the value attribute, then the value attribute will have type text.
If a Column Definition section has N data lines, then there will be one feature per every N values in the corresponding Column Data section with one value corresponding to one attribute.
The schema for a feature type from a column data section is determined by the corresponding column definition section. For example, if the mnemonics in the column definition section were mn1, mn2, mn3, then the attributes for the corresponding column data feature type would be mn1, mn2, mn3. The type of each attribute would be determined the same way as for a column definition/parameter data section: by looking through all the features for that feature type and seeing if they have a consistent type for that particular attribute; if not, then it defaults to text.
The reader will only produce one feature for the Other section, with exactly one attribute named wlas_other.
Thus the schema for the Other section is static and will always have one attribute of type text.
All features produced by this reader will always have geometry of type none.