Fault and top seal effectiveness has proved to be a significant risk in exploration success, and creates a large uncertainty in predicting reservoir performance. This is particularly true in the Australian context, but equally applies to exploration provinces worldwide. Seals can be broadly classified into fault, intraformational, and top seal. For geological time-scale processes, intraformational and top seals are typically characterised by their membrane seal capacity and fracture threshold pressure. Fault seals are typically characterised by fault geometry, juxtaposition, membrane seal capacity, and reactivation potential. At the production time scale, subtle variations in the permeability distribution within a reservoir can lead to compartmentalization. These are typically characterised by dynamic reservoir models which assume hydrostatic conditions prior to commencement of production. There are few references in the seals literature concerning the integration of hydrodynamic techniques with the various aspects of seal evaluation. The research for this PhD thesis by published papers includes: Methodology for characterising formation water flow systems in faulted strata at exploration and production time scales; a new theory of hydrodynamics and membrane (capillary) seal capacity; and case study evaluations demonstrating integrated multidisciplinary techniques for the evaluation of seal capacity (fault, intraformational and top seal) that demonstrate the new theory in practice. By incorporating hydrodynamic processes in the evaluation of total seal capacity, the evidence shows that existing shale gouge ratio – across fault pressure difference (SGR-AFPD) calibration plots need adjustment resulting in the calibration envelopes shifting to the centre of the plot. / This adjustment sharpens the predictive capacity for membrane seal analysis in the pre-drill scenario. This PhD thesis presents the background and rationale for the thesis topic, presents each published paper to be included as part of the thesis and its contribution to the body of work addressing the thesis topic, and presents related published papers that are not included in the thesis but which support the body of published work on the thesis topic. The result of the thesis is a new theory and approach to characterising membrane seal capacity for the total seal thickness, and has implications for an adjusted SGR-AFPD calibration to be applied in pre-drill evaluations of seal capacity. A large portion of the resources and data required to conduct the research were made available by CSIRO and its associated project sponsors including the CO2CRC.

Efficient management of limited water resources in an irrigation reservoir system is necessary to increase crop productivity. To achieve this, a reservoir release policy should be integrated with an optimal crop water allocation. Variations in hydrologic variables such as reservoir inflow, soil moisture, reservoir storage, rainfall and evapotranspiration must be considered in the reservoir operating policy model. Uncertainties due to imprecision, subjectivity, vagueness and lack of adequate data can be handled using the fuzzy set theory. A fuzzy stochastic dynamic programming (FSDP) model with reservoir storage and soil moisture of the crops as fuzzy state variables and inflow as a stochastic variable, is developed to obtain a steady state reservoir operating policy. The model integrates the reservoir operating policy with the crop water allocation decisions by maintaining the storage continuity and the soil moisture balance. The reservoir release decisions are made in the model in 10-day periods and water is allocated to the crops on a daily basis. On comparison with the classical stochastic dynamic programming (SDP) model and a conceptual operation policy model, it is observed that the FSDP model, in general, results in lower release from the reservoir while maintaining lower soil moisture stress. However the steady state reservoir operation policy obtained using the FSDP model may not perform well in a short-term reservoir simulation. A fuzzy state short-term reservoir operation policy model with storage and soil moistures of the crops as fuzzy variables, is developed to obtain a real time release policy using forecasted inflow and forecasted rainfall. The distinguishing features of the model are accounting for (a) spatial variation of soil moisture and rainfall using gridded rainfall forecasts and (b) ponding depth requirement of the Paddy. On comparison with a conceptual operation policy model, the fuzzy state real time operation model is found most suitable for the application of the short term real time operation for irrigation. The real time operation model maintains high storage in the reservoir during most of the 10-day time periods of a year and results in a slightly lower annual releases as compared to the conceptual operation policy model. The effect of inflow forecast uncertainty is examined using different sets of forecasted inflows, and it is observed that the system performance is quite sensitive to inflow forecast uncertainties. The use of the satellite based gridded soil moisture in the real time operation model shows consideration of realistic situations. Further, three performance measures, viz., fuzzy reliability, fuzzy resiliency and fuzzy vulnerability are developed to evaluate the performance of the irrigation reservoir system under a specified operating policy. A fuzzy set with an appropriate membership function is defined to describe the working and failed states to account for the system being in partly working and partly failed state. The degree of failure of the irrigation reservoir system is defined based on the evapotranspiration deficit in a period. Inclusion of fuzziness in the performance measures enables realistic representation of uncertainties in the state of the system. A case study of Bhadra reservoir system in Karnataka, India is chosen for demonstrating the model applications.

Reservoir economic performance is based upon future cash flows which can be generated from a reservoir. Future cash flows are a function of hydrocarbon volumetric flow rates which a reservoir can produce, and the market conditions. Both of these functions of future cash flows are associated with uncertainties. There is uncertainty associated in estimates of future hydrocarbon flow rates due to uncertainty in geological model, limited availability and type of data, and the complexities involved in the reservoir modeling process. The second source of uncertainty associated with future cash flows come from changing oil prices, rate of return etc., which are all functions of market dynamics. Robust integration of these two sources of uncertainty, i.e. future hydrocarbon flow rates and market dynamics, in a model to predict cash flows from a reservoir is an essential part of risk assessment, but a difficult task. Current practices to assess a reservoir’s economic performance by using Deterministic Cash Flow (DCF) methods have been unsuccessful in their predictions because of lack in parametric capability to robustly and completely incorporate these both types of uncertainties. This thesis presents a procedure which accounts for uncertainty in hydrocarbon production forecasts due to incomplete geologic information, and a novel real options methodology to assess the project economics for upstream petroleum industry. The modeling approach entails determining future hydrocarbon production rates due to incomplete geologic information with and without secondary information. The price of hydrocarbons is modeled separately, and the costs to produce them are determined based on market dynamics. A real options methodology is used to assess the effective cash flows from the reservoir, and hence, to determine the project economics. This methodology associates realistic probabilities, which are quantified using the method’s parameters, with benefits and costs. The results from this methodology are compared against the results from DCF methodology to examine if the real options methodology can identify some hidden potential of a reservoir’s performance which DCF might not be able to uncover. This methodology is then applied to various case studies and strategies for planning and decision making. / text