BHI Analysis integrated with Sedimentological and Structural Interpretations
Our detailed work has been undertaken with the benefit of many years of reservoir description experience worldwide and our borehole image expertise has been developed in tandem with our core-based sedimentological, petrographical, reservoir quality, structural and reservoir architecture skills.
As a result our staff are experienced in all facets of reservoir characterisation (eg. sedimentology/structure and borehole image interpretation), rather than focusing on the collection of borehole image data, in order to provide fully integrated and technically focused reports.
Data loading processing and QC
• QC of inclinometry data and tool dynamics.
• Speed correction conducted.
• Additional processing applied to enhance the images as required (pad normalisations, button equalizations, gain adjustments and EMEX corrections).
• Static and dynamic normalised images generated for each BHI dataset.
• Image quality of the processed images assessed and detailed using a simple traffic light code.
• Classification of manually picked surfaces into an image facies scheme representing bed-scale subdivisions that are calibrated with core lithotypes (where possible).
• Upscaling of image facies into genetically linked depositional packages or genetic elements based upon image facies content, log trends and stacking patterns.
Structural dip evaluation
• Structural dips calculated over intervals that are interpreted, on the basis of their BHI and wireline log signatures, to be in situ mudrocks and are validated by subsequent core calibration (where possible).
• Computed structural dips are applied to all picks in order to restore the original sedimentological dips so that the palaeoflow and the palaeoslope orientations can be more accurately determined.
• When the structural dip is not consistent along study successions, a structural zonation is generated by assessing the structural dip orientation and/or magnitude variations, using azimuth vector plots (aka. walkout vectors) of the selected facies.
• Post structural dip removal, the residual high-angle dips (eg. within cross-bedded sandstones) are analysed to define a potential palaeoflow orientation by reservoir/stratigraphic level within clastic reservoirs.
• The palaeocurrents can then be discussed at a field scale, where the results from all other directional datasets can be integrated within the overall geological model.
• Identification and classification of structural features based on image character.
• In situ stress indicators are categorised into breakouts and induced fractures to determine the maximum horizontal stress.
• Fractures are analysed according to their orientation to the defined stress and the implications for reservoir productivity are assessed.
Helical 3D CATscan analysis
• Circumferential images are loaded into the image analysis software and orientated using high-confidence picks on the BHI.
• Cored intervals can then be picked in detail using a scheme similar to the BHI image facies, but at a higher resolution and in a more refined way, ie. with input from core-based observations such as stratification type in aeolian systems.
• Provides enhanced core description with directional data generated for core-based features.
• Allows classification of bed contacts leading to an understanding of the hierarchy of key surfaces within the cored and uncored interval.
This high resolution A3 poster provides an overview of how we use Borehole Imaging data in Reservoir characterisation. (6.6mb)
The following case studies may be of interest:
The following articles may be of interest:
The following publications may be of interest:
- A sedimentological application of ultrasonic borehole images in complex lithologies: the Lower Kimmeridge Clay Formation, Magnus Field, UKCS
- Full-resolution 3D radar stratigraphy of complex oolitic sedimentary architecture: Miami Limestone, Florida, USA
- Fault and fracture prediction from coherence data analysis, a case study - The Magnus Field, UKCS
- Integrated Reservoir Characterization in Pursuit of a Heavy Oil Giant in the Arctic