Petrographic and isotope constraints on the origin of authigenic carbonate minerals and the associated fluid evolution in Late Permian coal measures, Bowen Basin (Queensland), Australia

Authigenic carbonate minerals are ubiquitous throughout the Late Permian coal measures of the Bowen Basin, Queensland, Australia. In the northern Bowen Basin, carbonates include the following assemblages: siderite I (delta O-18(SMOW) = +11.4 to + 17%, delta C-13(PDB) = - 5.3 to + 120), Fe-Mg calcite-ankerite-siderite II mineral association (delta O-18(SMOW) = +7.2 to + 10.20, delta C-13(PDB) = 10.9 to - 1.80 for ankerite) and a later calcite (delta O-18(SMOW) = +5.9 to + 14.60, delta C-13(PDB) = -11.4 to + 4.40). In the southern Bowen Basin, the carbonate phase consists only of calcite (delta O-18(SMOW) = +12.5 to + 14.80, delta C-13(PDB) = -19.4 to + 0.80), where it occurs extensively throughout all stratigraphic levels. Siderite I occurs in mudrocks and sandstones and predates all other carbonate minerals. This carbonate phase is interpreted to have formed as an early diagenetic mineral from meteoric waters under cold climate and reducing conditions. Fe-Mg calcite-ankerite-siderite Il occur in sandstones as replacement of volcanic rock fragments. Clay minerals (illite-smectite, chlorite and kaolinite) postdate Ca-Fe-Mg carbonates, and precipitation of the later calcite is associated with clay mineral formation. The Ca-Fe-Mg carbonates and later calcite of the northern Bowen Basin are regarded as having formed as a result of hydrothermal activity during the latest Triassic extensional tectonic event which affected this part of the basin, rather than deep burial diagenesis during the Middle to Late Triassic as previously reported. This hypothesis is based on the timing relationships of the authigenic mineral phases and the low delta O-18 values of ankerite and calcite, together with radiometric dating of illitic clays and recently published regional geological evidence. Following the precipitation of the Ca-Fe-Mg carbonates from strongly O-18-depleted meteoric-hydrothermal fluids, continuing fluid circulation and water-rock interaction resulted in dissolution of these carbonate phases as well as labile fragments of volcaniclastic rocks. Subsequently, the later calcite and day minerals precipitated from relatively evolved (O-18-enriched) fluids. The nearly uniform delta O-18 values of the southern Bowen Basin calcite have been attributed to very low water/rock ratio in the system, where the fluid isotropic composition was buffered by the delta O-18 values of rocks. (C) 2000 Elsevier Science B.V. All rights reserved.

Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.