Rock physics experts | DHI | Direct Hydrocarbon Indicators | Ikon Science

Direct Hydrocarbon Indicators - DHIs

With increasing availability of high quality seismic data, the search for and use of Direct Hydrocarbon Indicators (DHIs) during any exploration campaign has become commonplace.

However, not all DHIs are obvious and it is therefore crucial that before entering an exploration interpretation process, adequate time is spent determining the likely rock property behaviours and their seismic manifestations.

Figure 1 provides an illustration of such a case, where the hydrocarbon bearing reservoir becomes invisible on conventional stack data (Waters and Kemper, 2014).

Fig 1. Forward model litho fluid

By this means, the appropriate interpretation strategy can be designed and careful deliberate selection of seismic attributes can be made. Figure 2 shows a pseudo well, constructed from regional rock property trends.

These plots provide information on the typical AVO behaviours of reservoirs and provide insight into the anticipated changes in the seismic expression under different fluid bearing conditions and over a range of burial depths.

Knowing what to expect and when allows interpreters to focus on the most relevant geological intervals and seismic anomalies.




Fig 2. Pseudo Well from Trends

Ikon Science experts have a wealth of knowledge and experience. Combining sparce data with analogue datasets from the Ikon Science global portfolio of regional rock property studies helps guide Ikon Science customers during some of the most critical decision making processes.

By understanding both the geological environment and burial history, we can create rock property estimates for a range of diagenetic states using Ikon Science comprehensive rock physics modelling tools (Figure 3).

These in turn can be used to create synthetic seismic products which can be used to validate an interpretation.


Fig 3. Rock Physics and Diagensis

By analysing and making use of regional models and analogues and combining that with localised data, we are able to help create seismic products which illuminate lithological and fluid effects present.  Figure 4 shows results of a ‘conventional’ full stack interpretation, versus an interpretation made when prior information about the geology and rock physics was used to derive a lithology volume for interpretation. 

The green pick made from the lithology volume results in a different structural interpretation than derived from the full stack interpretation in pink. In this example, it is clear that there may be many instances where subtle hydrocarbon traps could be missed (Waters and Kemper, 2014). Armed with an atlas of rock property and seismic behaviours, your interpreters can make the most of their data and effort.


Fig 4. Relative AI and corresponding lithology