Stochastic Trap Analysis: Regional Validation of Traps in the Otway and Bass Basins

Abstract

Understanding exploration risk involves considering a range of factors including seal/trap efficiency, charge, and reservoir presence/quality. In many prospects risk analysis considers trapping hydrocarbons against faults. Typically the risk analysis is based on cross-fault juxtaposition and/or sealing shale development on the faults, on a single “best” technical model.

Many studies have focused on calibrating sealing shale development to predict Hydrocarbon Water Contacts, and a commonly used algorithm for seal on faults is shale gouge ratio (SGR). These calibrations involve back-calculating the seal potential as SGR and determining a resulting across fault pressure difference or capillary entry pressure. In almost all studies, this back-fitting of SGR and seal capacity has been conducted on single “best” technical models with no direct modelling of uncertainty. In general, application of SGR methods on sealing potential across faults in exploration prospects increases predicted column heights relative to juxtaposition-only heights, and thus enhances the apparent pre-drill chance of success. If wells do not find the predicted columns, this is often “explained” by lack of charge or trap breach. It is proposed that the fault and stratigraphic uncertainties are significant and need to be included in the modelling of fault seal risk and inferred column heights. A process of model validation will be presented in which observed hydrocarbon water contacts are compared with probabilistic models for both juxtaposition and SGR.

A comprehensive review of the gas fields of the Otway and Bass Basins show that probabilistic models can accurately predict hydrocarbon water contacts with a high degree of accuracy. The probabilistic analyses identify cross fault leak elevations and potential stratigraphic thief zones. Several discoveries in these basins, including La Bella, Minerva, Yolla, Geographe and Thylacine, were analysed.

Probabilistic juxtaposition models better predict hydrocarbon water contacts and are thus superior for prospect fault seal risk analysis than models such as SGR. Incorporating uncertainties in a stochastic analysis typically generates smaller, lower risk traps, rather than large, high risk traps. Applying these models and methods to fault seal analysis will allow explorers to better define risks and rewards on prospects.

AAPG Datapages/Search and Discovery Article #90323 ©2018 AAPG Annual Convention and Exhibition, Salt Lake City, Utah, May 20-23, 2018