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The Carman-Kozeny formulation has been used as a basis to provide a new perspective of flow zone units (FZUs), by mapping similar rocks in terms of "Characteristic Envelopes", for different geological depositional environments. A large amount of data, covering several fields and different Australian basins, has been analysed. The methodology has been used for well-to-well correlation, reverse modelling for better identification of depositional trends, diagenetic affects and grain characteristics. It is also shown how photomicrographs, scanning electron micrographs (SEM), and log shapes can be incorporated in a detailed analysis. The method is ideal for validating plug samples used in special core analysis. It is shown how various data types, geological attributes and engineering parameters can be integrated. Results from such analysis can then be used in consistent model preparation and better quantification of petroleum recovery efficiency. Introduction Prediction of recovery efficiency and petroleum reservoir productivity is an important task for petroleum engineers, requiring detailed analysis of various reservoir properties and their interrelationship. To be successful, such reservoir description and analysis requires the integration of geological and engineering parameters. Core description and analysis gives information about pore structure and their characteristics, where the geometry is the end result of a long geological process involving deposition and diagenesis. Geoscientists have traditionally classified rocks according to porosity, grain size and distribution, grain sorting, mineralogy and petrophysical parameters, whereas reservoir engineers tend to emphasize the flow behaviour of rocks. The Carman-Kozeny (C-K) equation may be used to bridge this gap, considering variation in flow behaviour as a function of geological facies, the correlation parameter being the hydraulic radius. For a particular reservoir, various layers or facies may be grouped together to form Hydraulic Flow Zone Units (FZUs) or Hydraulic Units (HUs). This paper provides a new perspective of FZUs, by mapping regions or envelopes in the C-K space, for different geological depositional environments, analysing a large amount of data from a number of fields and covering several Australian basins. "Characteristic Envelopes" may be seen as a key feature in FZU modelling and they can be defined for very specific situations, with envelope boundaries covering a limited or entire depth range, including diagenetic variation. HU composition inside each envelope may thus reflect sorting, compaction, variation in grain characteristics, pore structure, and energy of deposition for the particular depositional environment under consideration. More generally, major depositional environments, for example channel environments, have been grouped for comparison, covering different parts of the C-K domain and demonstrating individual quality. The definition of each envelope has been derived by analysing similar depositional sequences for several fields, showing good agreement. To further verify and validate this approach, particularly for non-uniform intervals, use has also been made of log shapes and petrographic (also SEM) images and several of these are given to demonstrate the concepts. Finally, the outlined methodology may be used as a prediction tool for the case of a new geological province, where a particular geological environment has a certain chance of occurrence. In this case, a specific envelope may be considered, to predict possible formation characteristics, and related porosity, permeability and other property values. Study results may be used in prediction of recovery efficiency and reservoir/well productivity. The described methodology is also compared to other methodologies.

A case study of the Spring Gully coal seam gas (CSG) field illustrates how an integrated production data management and analysis system has consolidated scattered data sources into a unified repository to provide easy access for reporting and analysis. Automated surveillance workflows with notification and alarm capabilities have simplified production performance tracking and enabled proactive decision making. Current analysis techniques and expert knowledge have been captured in predefined templates and workflows to identify trend violations, flagging the issues and optimizing production. The new system has provided a foundation layer for managing the production and deliverability of thousands of wells now and in the future, helping to translate data into information. Enabling timely decision making through the use of accurate, validated data and automated workflows has helped engineers focus on problem solving and analysis. The streamlined process will continue to help the operator's CSG teams improve the efficiency and productivity of all their assets.

Laboratory derived capillary pressure data can be seen as an important tool for the purpose of establishing water saturationheight relationships as a function of rock type, forming the basis for a number of petroleum engineering and geoscience estimates. A modified 'FZI-λ' method, capable of giving better estimates of fluid distribution for Australian reservoirs, is proposed. The new methodology is particularly well suited for interpolating among different lithologies and diverse rock types as evident from a comparison with other methods reported in the literature, using a case study of the Griffin area fields.Reconciliation of capillary pressure data with core and log data can be advantageous for better reservoir description. In this work, the Carman-Kozeny (C-K) equation based Hydraulic Flow Zone Unit (HU or FZU) methodology has been found ideal in characterizing geologic depositional environments and modelling fluid saturation profiles. For this purpose, the concept of 'Global Characteristic Envelopes' (GCEs) has been introduced, to analyse geological and petrophysical characteristics and for the integration and correlation among the wells. Capillary pressure data, based on such FZU and depositional grouping, may be further used for modeling saturation profiles over the uncored intervals and allows meaningful averages to be assigned for geocellular modeling and reservoir simulation.

Intelligent Completions (IC) are deployed with the high hopes of frequent data utilization and zonal selectivity maneuver to optimize production continuously. The permanent downhole presence of measurements like pressure, temperature, rate, water-cut, gas-break provide downhole indicators and trending analysis of production performance and injection conformance. These are utilized not only to maximize hydrocarbon production but also to reduce surface handling of water and/or gas, improve injection efficiency, and reduce carbon and environmental footprint. However, the reality could be different from the evaluation stage to the application stage. The asset production engineers or the reservoir engineers face real challenges when it comes to design, downhole installation, data transmission, real-time analysis, and optimization to deliver the real value of the initial investment. These suboptimal application factors, multiplied by the complexity of IC deployment and execution with existing hardware constraints, have limited the progression towards digital well technology. By analyzing such trends, a new advanced completion optimization methodology has been devised, leveraging the latest technology and innovation, IC deployment simplification, and electrification efforts in the industry. This paper analyses the underutilization reasons of digital well technology, such as - the ability of design and implementation, the downhole data measurement, complexity of modeling and optimization, and the bottlenecks in applying the learning from the Intelligent Completions data to optimize production. It is then compared to the easing transition to the future digital-wells, advanced modeling capabilities that are driving the oilfield digitalization by next-generation Intelligent Completion. This digital transition ranges from ease-of-deployment to ease-of-optimization and eventually towards cloud-enabled decision making. The new era of IC electrification deployment and digital solutions are twinning to provide an integrated platform to maximize value and justification for more future digital wells. A fully digital system to control reservoir and optimize the product is becoming a reality with the transformation of modeling capability and enabled by simplification of IC deployment, and this is the digital future of IC optimization. This digital solution is continuously feeding asset subsurface, modeling, and optimization team with productivity or injectivity indexes and other inputs required for reservoir steady-state and transient evaluation. The IC industry continues to be integrating into the new solution frontiers of logging-while-producing, the testing-while-producing capability to the eventual optimizing, modeling-while-producing future, leading towards a true digital oilfield of the future.