Luca Colombera, Nigel P. Mountney, William D. McCaffrey

1. Analogue-based correlability models for fluvial successions: a tool for guiding and ranking subsurface interpretations Luca Colombera, Nigel P. Mountney, William D. McCaffrey Fluvial & Eolian Research Group – University of Leeds

2. Correlation of fluvial channel bodies Well correlations of fluvial channel bodies in successions hosting hydrocarbon reservoirs or aquifers often rely on predictive empirical relationships for forecasting lateral extent of individual bodies. Yet, it is necessary to consider sampling of natural variability as an element for evaluating geological realism. Collinson (1978) He et al. (2013)

3. Overview Application of a relational database for the digitization of fluvial sedimentary architecture – the Fluvial Architecture Knowledge Transfer System (FAKTS) – to informing well correlation of fluvial channel bodies • Quantitative characterization of fluvial architecture applicable to: • develop quantitative facies models • genetic studies of fluvial architecture • derive constraints to subsurface well correlations • derive constraints to stochastic reservoir models

4. FAKTS database Relational database for the digitization of the sedimentary and geomorphic architecture of classified fluvial systems. Stored data include: types, geometries, spatial relationships and hierarchical relationships of three order of genetic units. Here, focus is on large-scale depositional elements. after Colombera et al. (2012)

5. Data Entry Part of panel from Olsen (1995) Depositional elements classified as channel-complex or floodplain element, and distinguished geometrically. Published summary data also included. Part of panel from Dalrymple (2001) Part of panel from Hirst (1991) Labourdette (2011) Part of panel from Hajek et al. (2010) 118 case studies including 32,647 classified genetic units: 7,522 classified depositional elements 3,479 classifified architectural elements 21,646 classified facies units 178 unit groups with descriptive statistics

6. Traditional analogue approaches Evaluation of traditional empirical relationships for guiding correlation of individual fluvial channel bodies. Empirical relationships linking channel-body width to formative channel depth through channel-body thickness (cf. Collinson 1978) or linking channel-body width to thickness (cf. Fielding & Crane 1987) have limited predictive power due to their inability to account for variability.

7. Traditional analogue approaches Derivation of empirical relationships to be used as constraints to well correlations and more generally as predictive models of subsurface architecture.

8. Channel-complex correlability models Traditional methods to guide well-to-well correlations are based on constraints relating to individual units. – We propose a probabilistic approach based on patterns of correlability recognized in reservoir analogs. The method can be used to quantify the geologic realism of a subsurface correlation panel as compared to an outcrop/synthetic analog.

9. Channel-complex correlability models The method is applicable to well arrays with constant well spacing and to any genetic-unit type for which the lateral-extent distribution is known. Total probability of penetration f(well spacing) Total probability of correlation f(well spacing) For lognormal pdf’s (e.g. channel complexes):

10. Channel-complex correlability models Correlability models express the likely proportion of penetrated units that are also correlatable over a given distance. saidbisd Comparison with correlability models will quantify the geologic likelihood of a correlation panel and tell us how to improve it.

11. Example application: Travis Peak Fm. Example use: ranking the geologic realism of 3 alternative correlation panels (Travis Peak Fm.).

12. Example application: Travis Peak Fm. Example use: ranking the geologic realism of 3 alternative correlation panels (Travis Peak Fm.).

13. NTG-based empirical relationships Possibility to quantify the degree of association of different architectural properties.

14. NTG-based correlability models Correlability models based on NTG-based empirical relationships. Draw values for appropriate well-spacing and multiples Bespoke correlability model

15. Application of relationships to SIS Information on channel-complex width standard deviation, mean and channel-complex proportion can be used to inform indicator variograms for the cross-stream direction. Channel-complex indicator variograms for horizontal cross-stream direction

16. Application of relationships to SIS Informing Sequential Indicator Simulations on NTG-based empirical relationships. 10% model FAKTS-based validation

17. Conclusions • Large architectural database (FAKTS) of classified fluvial systems permits generating empirical relationships for guiding channel-body correlation, and assessing their predictive value. • Probability-based correlability models can be generated for guiding and ranking correlation panels of channel complexes, in a way that allows for consideration of natural variability. • Database-derived empirical relationships linking NTG to channel-complex geometries can be employed to generate NTG-based correlability models. • The same NTG-based relationships can be used for informing horizontal indicator variograms with which to constrain Sequential Indicator Simulations. • Correlability models can be generalized for any angle of well penetration and can be compiled for any genetic-unit type.