ASEG Extended Abstracts - 25th International Conference and Exhibition – Interpreting the Past, Discovering the Future, 2016

There 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 3040%. 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.

The Capricorn Orogen Passive source Array (COPA) is the passive source seismic component of a major Science and Industry Endowment Fund (SIEF) project, “The distal footprints of giant ore systems: Capricorn case study”. COPA focuses on the deep crustal and shallow lithospheric structure in the Capricorn Orogen with the aim to better understand the tectonic amalgamation of the Western Australian Craton. The objective of COPA is to produce 3D multiple scale seismic images across the orogeny, that together with other geological and geophysical datasets help constrain the timing and kinematic evolution of Capricorn Orogen’s fault zones, and their role in the metallogenic history.

An integrated interpretation of potential field and magnetotelluric (MT) data was performed in the east Kimberley, northern Western Australia Structural interpretation of potential field data was constrained by geological field observations, petrophysics, remote-sensing and an understanding of the tectonic history of the region. Forward modelling of the potential field data located along the same survey traverse as the magnetotelluric data allowed comparison between the two datasets to assess complementarity of images and assist interpretation. Interpreted features include the presence of large-scale structures and associated electrical anomalies that indicate the presence of mineralisation deep in the crust, and guide prediction of mineralisation at or near the surface. The King River Fault is revealed to be a crustal-scale, west-dipping structure, which footwall bounds the western side of a large resistive body. A conductive anomaly is also located on the hanging wall of the King River Fault. A number of scenarios are discussed to the source of conductivity, including the presence of sulphides, saline water and graphite. Our assessment suggests that graphitic rocks, most likely with some sulphide content, contribute to the strength of this anomaly, and highlights the known potential of the east Kimberley to host graphite deposits. The conductive anomaly has a spatial and geometric correlation to Speewah Dome, a known prospective region. The depth of the conductor (c. 5km) precludes mining, but does indicate King River Fault is likely to form a mineralising conduit, and may contribute to possible Pb-Zn mineralisation where the fault reaches the surface.

Airborne electromagnetic (AEM) data are an immensely useful tool for mapping cover thickness and under cover geology in Australia. The regional AEM surveys conducted by Geoscience Australia (GA) and other agencies are an ideal starting point for integrating legacy AEM datasets across a range of scales with other information, e.g. borehole stratigraphy and shallow seismic data, as part of a national cover thickness map. Geoscience Australia is working towards this end as part of the UNCOVER Initiative.

Ultrasonic pulse velocity method is a standard method for measuring elastic properties of rock cores in laboratories. Cylindrical plugs of 40-100 mm length are usually used for such measurements. It was recently shown that thin disc samples (~15 mm in length) were suitable for such measurements in the case of an advanced experimental set-up. Here we present results of numerical simulations to support the outcome of the previous work and to improve the understanding of wave propagation in the samples during laboratory ultrasonic measurements. The finite element method within Abaqus/Explicit (Dassault Systemes, Simulia) is used to simulate wave propagation along the experimental rig and the rock sample caused by transmitted ultrasonic pulse. The computational domain mimics the real geometry. The results of the numerical modelling prove that an S-wave transducer also produces a compressional wave that propagates along the sample and can be recorded by a receiver. Simulations are performed for three configurations used in real laboratory experiments. The numerically simulated waveforms are compared with the signals, recorded during laboratory experiments. Simulated travel times of elastic waves are in a good agreement with experimentally obtained results.

Independent Simultaneous Source (ISS®) technology is an attractive way to provide high acquisition production rates and affordable higher density seismic imaging. In this paper, we propose an advanced deblending scheme to address the source separation requirement of ISS® data. The deblending scheme includes a) 3D low-rank decomposition based iterative noise modelling, and subtraction, b) signal-to-noise ratio map guided residual denoise and c) erratic noise attenuation. The application is tested on actual shallow water OBC dataset, which was pseudo-blended using a realistic dual vessel acquisition plan. The result shows that this advanced deblending scheme can successfully recover individual source responses. The deblended data have a minimal difference compared with the actual unblended data.

Time-lapse (4D) seismic data sets have proven to be extremely useful for reservoir monitoring. Seismic-derived impedance estimates are commonly used as a 4D attribute to constrain updates to reservoir fluid flow models. However, 4D seismic estimates of P-wave impedance can contain significant errors associated with the effects of seismic noise and the inherent instability of inverse methods. These errors may compromise the geological accuracy of the reservoir model leading to incorrect reservoir model property updates and reservoir fluid-flow predictions. To evaluate such errors and uncertainties we present a time-lapse study based on a 3D reservoir model example, thereby exploring a number of inverse theory concepts associated with the instability and error of coloured inversion operators and their dependence on seismic noise levels. In this example, we use an oilfield benchmark case based on the Namorado Field in Campos Basin, Brazil. We introduce a histogram similarity measure to quantify the impact of seismic noise on maps of 4D seismic amplitude and impedance changes as a function of S/N levels, which indicate that amplitudes are less sensitive to 4D seismic noise than inverted impedances. The root-mean-square errors in the estimates of water saturation changes derived from 4D seismic amplitudes are also smaller than for 4D seismic impedances, over a wide range of typical seismic noise levels. These results quantitatively demonstrate that seismic amplitudes can be more accurate and robust than inverted seismic impedances for quantifying water saturation changes from 4D seismic data, and emphasize that seismic amplitudes may be more reliable to update fluid-flow model properties in the presence of realistic 4D seismic noise.

Rotating the gravity gradient tensor about a vertical axis by an appropriate angle allows one to express its components as functions of the curvatures of the equipotential surface. The description permits the identification of the gravity gradient tensor as the Newtonian tidal tensor and part of the tidal potential. The identification improves the understanding and interpretation of gravity gradient data. With the use of the plunge of the eigenvector associated with the largest eigenvalue or plunge of the main tidal force, it is possible to estimate the location and depth of buried gravity sources; this is illustrated in model data and applied to FALCON airborne gravity gradiometer data from the Canning Basin, Australia.

Logging through drill rods and casing is a well-known challenge in the coal, oil and gas industries, and several techniques have been developed to obtain open-hole values using open-hole tools in cased-hole (C-thru). Due to the differences between conventional open-hole and iron ore environments and practices, simply applying the same methods can result in spurious data and unreliable findings.

A revised tool design together with an improvement upon the standard oil and gas technique through single wall rods was required to ensure accurate results. Development of an appropriate compensation algorithm and response through Reverse Circulation (RC) rods was determined where multiple walls of steel and gaps of fluid and air separate the tool from the target formation.

For engineering applications involving fluid flow through porous rocks underground, the permeability of a rock mass is an important parameter. Imaging of the 3D permeability distribution is generally done by a history-matching approach: fluid pressure due to injection in a well with known pressure and flow rates is numerically simulated, and the rock permeability is adjusted so as to match predicted pressure values to measured observations. These pressure observations are made at producing wells. Because there will normally be few wells, the observations, while being dense in time, are spatially sparse. The idea of this paper is to augment these downhole pressure measurements by using microseismic data to infer pressure at seismic event locations.

The mechanism of pressure-induced seismicity is the reduction of effective normal stress across a plane of weakness. The rock strength can be represented as a critical pressure - the pore pressure above which the rock will fail. The rock strength is highly heterogeneous, because of the existence of weaknesses such as joints, bedding planes, and clay bands, and stronger regions such as sandstone channels. So the rock strength will be random. We model the rock strength as a Weibull-distributed critical field. A microseismic event occurs where pressure exceeds this critical field, and so is effectively a point pressure measurement, with an uncertainty given by this Weibull distribution. The idea is to augment the well-pressure observations with these “virtual” pressure measurements at seismic event locations.

We model pressure diffusion using a finite volume approach, and examine the inversion, for permeability, of two different types of data, (1) pressure measurements in boreholes, and (2) virtual pressure measurements at seismic event locations. We show that the two types of data provide complementary information.

Over the last few years exploration activity in Papua New Guinea (PNG) has declined to alarming lows that the Mineral Resources Authority (MRA) has introduced initiatives to acquire new geo-scientific datasets to enhance exploration in the country. One such initiative has been the 30,000 plus line kilometre airborne magnetic and radiometric survey over the western part of the country. The airborne survey was strategically located between the large Ok Tedi porphyry copper-gold mine and the advanced Frieda River porphyry copper-molybdenum prospect. The airborne datasets were acquired at a north-south line spacing of 500m with a Tie-line spacing of 5km and at nominal terrain clearance of 100m.

The main aim of the airborne geophysical survey was to identify magnetic and radiometric anomalies that may be further investigated for their mineral potential. Preliminary results of the airborne survey show large deep-seated NW-trending fault systems cross-cut by north-east trending transfer structures that may have contributed to mineral deposition in the region. Several magnetic and radiometric anomalies located within the periphery of existing prospects also have the potential to substantially increase resource values, while isolated anomalies may indicate new targets for further exploration.

While this paper highlights some of the interesting magnetic and radiometric features defined from the WPAGS, the release of the datasets now ensures investors have an extra layer of information to build on the mineral potential of the surveyed area. It is anticipated that the results from the survey will not only boost interest to explore in the area, but also drive exploration activities in the area to new heights, hopefully resulting in the identification of new mineral prospects.

Total organic carbon (TOC) is directly associated with total porosity and gas content and is a critical factor in assessing the potential of unconventional reservoirs. TOC content is only known at the depths where the laboratory measurements on recovered core samples are performed. However, reliable estimation of potential resources can only be based on information about vertical and lateral distribution of organic matter throughout the prospective gas shale reservoir. This information is commonly obtained from conventional wireline logs, such as gamma ray, density, transit time and resistivity. Due to the complexity of unconventional reservoirs, traditional methods based on distinct differences of resistivity, density and sonic velocity of organic matter from those of the inorganic matrix are not always successful. We investigate the best way to predict the TOC using gamma-ray, density, porosity, resistivity and sonic transit time log responses by applying machine learning methods such as Artificial Neural Network (ANN) and Support Vector Machine (SVM). The analysis is done on the data from seven wells drilled through onshore unconventional reservoirs in the McArthur Basin (Northern Territory) and Georgina Basin (Northern Territory and Queensland), Australia. The prediction quality of traditional, multiple liner regression (MLR) and machine learning methods was compared. The most accurate TOC estimates were generated by ANN- and SVM-based nonlinear predictors, followed by the MLR and traditional models. This indicates that geologic complexity affects the relationship between the log response and TOC in the area of interest.

Horizon mapping using magnetic data was conducted over a part of the Western Papuan Fold Belt, in an area of rugged terrain, where the geological structures are of relatively low complexity. Energy spectral analysis was used to detect magnetic susceptibility contrasts that were laterally merged to form magnetic interfaces corresponding to horizons derived from seismic and well data.

Numerous magnetic interfaces were detected corresponding to: magnetic layers within the Darai Limestone, top of Ieru Formation, intra-Ieru and deeper intra-sedimentary boundaries. These mapped sedimentary surfaces form an anticlinal structure which plunges towards the south-east. A major thrust fault, mapped from magnetic data using automatic curve matching, truncates the anticline in the south-west. Sedimentary magnetic layers were mapped on both sides of this fault. The results obtained from the interpretation of the magnetic data are consistent with structures mapped from seismic and well data.

The reprocessing of legacy seismic data can be a time and cost effective means of obtaining an improved image of the subsurface, particularly when compared to the acquisition of new seismic data. The investment that has been made over the years in acquiring the many thousands of kilometres of seismic data offshore Australia has been preserved by Geoscience Australia, which houses an extensive collection of petroleum data including seismic survey data. Much of this data is available to the petroleum industry for reprocessing, facilitating the potential to enhance the data’s value for regional reconnaissance and interpretation.

Two marine examples are shown from North West Shelf Australia where reprocessing was performed on seismic data from two different surveys acquired in 1993. The first example is from the Northern Carnarvon Basin, and the second example is from the Browse Basin.

These two examples demonstrate how the uplift attained from a modern broadband processing flow can yield a vastly improved subsurface image, which in turn can assist with interpretation. The reprocessing workflow (which was similar for both surveys) is discussed, as well as some insights into how the improved data benefit the interpretation and understanding of subsurface geology.

The Capricorn Orogen is located in central Western Australia and includes several Proterozoic sedimentary basins. The Yerrida and Earaheedy basins are located in the south-east of the orogen and were formed, and deformed, over multiple orogenic events. The complexity and thickness of these basins and presence of conductive regolith has hindered minerals exploration within the region. A recently acquired TEMPEST AEM survey across the Capricorn provides an extensive dataset to aid in the mapping of the basin lithologies and assessment of the potential for mineralisation within these basins. Before detailed interpretations can be made from 1D inversions of these data, an understanding of the reliability of TEMPEST AEM inversions is desirable.

1D time-domain inversion algorithms are useful for interpreting TEMPEST AEM data. However, it is important to understand the limitations of using such codes in geologically complex regions such as the Capricorn Orogen. The response from three simple scenarios involving a dipping conductive contact within a resistive basement, and a dipping conductive contact under a varying conductive regolith have been inverted using a 1D layered earth algorithm. Results show that conductive units in a resistive host dipping steeper than 25^o are poorly resolved. When moderately conductive to resistive cover is present, the dip and thickness of dipping features can be defined, however, this is dependent on the depth of the conductive unit. Knowledge of the limitations of 1D AEM modelling provides some confidence for making geological interpretations from 1D inversions, as falsely resolved dipping features can be eliminated from the interpretation process.

Seismic recording equipment engineering and manufacturing has experienced an evolutionary change in the past 20 years. In addition to great strides in channel count and flexibility, the cost per channel has also dropped steadily. Seismic contractors utilizing modern equipment can economically shoot in virtually any region that can be accessed with little or no lasting impact on the land and at the same time the quality and utility of the recorded data has increased inversely to the cost.

These evolutionary strides are supported by higher channel counts; lighter more flexible equipment and advances in source technology including operational strategies which produce 20,000 or more source points in a single day of shooting. The growing trend of high density single point sources combined with single point sensors is yielding high fold data of unprecedented quality.

This presentation will explore the more recent advances in seismic equipment development and the operational changes they have enabled to deliver this evolutionary change in the quality and cost of seismic data.

IP measurements in airborne EM data have not been previously considered for mapping groundwater distribution. IP modelling can be applied to discriminate between co-existing salty aquifers (conductive and non-chargeable) and extensive clay layers (conductive and chargeable); typical in both coastal areas and regions affected by dry-land salinity. The current case study presents the field results from a gold and metal project that had a hydrogeological mapping component to it in central Western Australia. Accounting for IP signal in the forward response was necessary to fit the data in localised areas, which were then interpreted as clay filled (conductive and chargeable) palaeochannels. The synthetic experiments that followed confirm that in favourable conditions, clay derived IP signal can affect the measured AEM response. Conversely, IP information can be recovered from these data, providing an extra physical parameter of value to the hydrogeological interpretation.

Seismic data collected in volcanic rocks coverage area has weak energy and low signal to noise ratio. These characteristics cause severe problems for seismic exploration. Many geophysicists try to solve these problems and propose many methods. Some of them focus on the acquisition method to improve the signal to noise ratio of data in the step of data acquisition. The others focus on the processing method to improve the data .In this paper, we focus on the processing method and try to apply the seismic interferometry to volcanic rocks coverage collected on the periphery of Songliao Basin to improve the signal to noise ratio and the resolution.

Mineral deposits are associated with geological settings characterized by discontinuities and complex structural heterogeneities such as fracture zones, small-scale objects, intrusive and steeply dipping structures. Therefore, detecting such heterogeneities is of primary interest in mineral exploration. Usually, the scale and shape of such heterogeneities cause the seismic energy to diffract rather than reflect. Despite the natural lack of reflectors and potentially abundant number of diffrators, there are only few case studies of diffraction imaging in hard rock environments with almost no examples of diffraction imaging in prestack domain. Herein, we fill this gap by implementing a 3D prestack diffraction imaging technique to detect point diffractors in hard rock environment. The technique includes computation of diffraction traveltime curves followed by semblance analysis along the curves, with high value of semblance corresponding to high diffractivity.

The performance of the method is demonstrated on a 3D synthetic seismic data and applied to a 3D field seismic data set recorded over Kevitsa mineral deposit in the northern Finland. The results of the 3D prestack diffraction imaging method suggest that diffractivity is a powerful attribute that can be used with other seismic attributes for the interpretation of seismic data in hard rock environments.