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GCA New Approach to Stratigraphic Interpretation*
Farrukh Qayyum1, Nanne Hemstra1, and Paul de Groot1
Search and Discovery Article #41195 (2013)
Posted September 16, 2013
*Adapted from the Geophysical Corner column, prepared by the authors, in AAPG Explorer,
September, 2013.
Editor of Geophysical Corner is Satinder Chopra ([email protected]). Managing Editor of AAPG Explorer is Vern Stefanic
1dGB Earth Sciences, Enschede, Netherlands ([email protected])
This article introduces a new set of seismic
attributes that play an important role in extracting detailed stratigraphic information from
seismic
data. The attributes in question are derived from a HorizonCube, one of the emerging interpretation techniques that provide fully interpreted
seismic
volumes (Figure 1). In this particular technique, horizons are automatically tracked between a given set of framework horizons and faults. The tracking is done using a
seismic
dip volume.
Compared with conventional amplitude tracking, this algorithm is more robust in areas with low signal-to-noise ratio, where diachronous events can be tracked as well as events that are phase inconsistent. As these horizons are guided by a continuous dip-field, they may converge and diverge according to the dip of a seismic
reflector. In this way, the key geologic features such as unconformities, pinchouts and condensed sections are highlighted. Horizons can be tracked in two different modes (Figure 1):
- As continuous horizons that stay together when they converge and never cross each other. Such horizons help identify unconformities and condensed sections – particularly useful in 3-D attributes visualization and reservoir
modeling
.
- As truncated horizons that may stop when they meet each other in space based on a user-defined threshold. This helps to identify stratigraphic lapouts (onlaps, downlaps and top laps). These also are useful in Wheeler diagram creation and sequence stratigraphic interpretation.
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New Family of Stratigraphic Attributes For the continuous set of ![]() ![]() ![]() ![]() ![]() ![]() From a stratigraphic interpretation standpoint, the mapped Typical attributes that are extracted using this sequence stratigraphic framework include stratigraphic unit IDs (identification number) and isochrons. The IDs of interpreted stratigraphic units can either be unique (each systems tract unit is assigned a unique identification number) or common (each identical systems tract is assigned a common number). An isochron attribute calculated the thickness of a stratigraphic unit. The unit of this attribute depends on the The relative rate of preservation – the ratio between an isochron volume and a known geologic time-span for a particular unit – also can be calculated with the results being relative measurements of the rate of preservation per geological time unit. Finally, an attribute can be generated that defines the difference between two isochron grids as a volume at a certain trace location. Example: Extracting Deepwater Channel Stages During the Neogene Period, the Carnarvon Basin in the Australian Northwest Shelf comprised several deepwater meandering channelized systems. One of those systems is studied using the new stratigraphic unit ID attribute. To our knowledge, this is the first study in which this attribute was used to define an unconventional set of stratigraphic units. Convention nomenclatures are not adopted, as the interval may fall in one systems tract. Therefore, a further subdivision of channel system requires a new sequence model. In this case, a “channel stages” sequence model is defined. It contains a set of N stratigraphic units defined as channel stages. Each unit is defined by its own unique ID. Upper and lower boundaries of the channel system were manually mapped to form an initial framework to process the densely mapped set of Five channel stages can be seen in Figure 2. The same interval also can be studied using the density attribute (Figure 3), which clearly shows channel base, levees and banks of channel systems. Workflows such as these support building better stratigraphic models to predict reservoir quality sands and to perform reservoir characterization. Dense sets of |