The Pelarang Anticline is part of the NNE-SSW oriented Samarinda Anticlinorium, a detached thrust-and-fold belt in the Tertiary Kutai Basin. Results from an airborne gravity gradiometer survey over the Pelarang Anticline are presented herein. The Pelarang Anticline is interpreted as a detachment fold ~30km long with steeply dipping (70 o-80 o) flanks. However, seismic imaging on existing 2D data is poor. In October 2016 Cue Energy acquired airborne gravity gradiometer survey data over the anticline. The survey revealed a large (~10mGal) gravity signal range, and that the anticline is associated with a strong, positive gravity anomaly. Subsequent application of potential field enhancement filters clearly delineated the crest and the flanks of the feature. 2D modelling of selected profiles across the anticline suggests that it can be modelled as a 1,500m-2,000m wide, by ~2,000m high shale body that is close to breaching the surface in places. This is in alignment with an interpretation that the feature is cored by highpressure shales, resulting in un-prospective areas. However, 3D modelling has revealed significant along-strike variations in the depths to the crest of the anticline, suggesting the presence of several anomalous structural lows. Further investigation suggests these features are pull-apart mini-grabens, formed in response to localized shear movements. At least two commercial hydrocarbon accumulations, Sambutan and Mutiara, appear to be genetically related to the newly recognized structural anomalies. This survey has led to the recognition of a new exploration play in the region, and provided a tool to pursue it.

In all exploration processes, the evaluation of basins, permits, and individual prospects changes over time with incremental availability and quality of data, technical effort expended, and knowledge gained. The NU prospect, located in the Mahakam Hilir PSC (East Kalimantan), is an example in which geologic chance of success (GCOS) predictions can change over time with increasing acquisition and availability of geophysical and geologic data and the studies done on them. We show how studies done on any one prospect or group of prospects can progressively increase/decrease the chance of at least one success in an exploration campaign of several wells. After a series of four wells was drilled in the PSC, which did not deliver commercial success, a change in approach was required to continue exploration. This included the acquisition of airborne gravity gradiometry data, initial trial prestack depth migration (PSDM) reprocessing of two key 1989 vintage 2D lines, acquisition of vintage well data from four Sambutan Field wells, acquisition of nine vintage 2D seismic lines over the field, and PSDM reprocessing of the nine 2D seismic lines. All data were then integrated to build a new geologic model. As a result, the NU prospect GCOS progressively moved from less than 10% to nearly 40%.

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SUMMARYThere is much confusion in the conceptualisation and application of Chance of Success (COS) Predictions in oil and gas exploration. Although the basic statistical underpinnings of COS predictions are not mathematically complicated, in practice, there appear to be significant difficulties. The consequences of this in many cases include misplaced expectations and hence morale problems from results of exploration which fall outside expectations. In reality, commercial exploration success rates worldwide range from 30-40%. So, there is more pain than not in our industry with the unfolding of expectations. As a result of this, companies have many times reacted in a knee jerk fashion to 'correct' their course which sometimes results in restructuring exploration teams and also changing the course of exploration. Much of the misunderstandings appear to arise from the fact that most small companies are involved in limited trials campaigns where budgets allow the drilling of only a handful of wells over 1-5 years. Realistic COS' can only be based on expectations related to drilling a statistically significant large number of wells. In this paper the vagaries of the actual unfolding of exploration results are simulated using MS Excel software's Random Number Generator function. Despite the intrinsic difficulty of not being able to guarantee any specific success, it will be shown how companies can choose the COS range they should be involved in to enable sustainable growth over the longer term.All the concepts and thoughts presented here are those of the author's and do not necessarily represent the author's employer Cue Energy's views on this matter.