Petrophysical facies modeling plays a key role in reservoir characterization at all levels. At a well level it helps to delineate the layers on basis of certain similar rock physics characteristics, which further can be used in reservoir engineering computations that include layer wise input of properties. At a field level petrophysical facies helps in mapping of reservoir units in a multi-well scenario. Pressure transient tests are performed to determine the reservoir properties like horizontal permeability (Kh), vertical permeability (Kv), skin, knowledge of reservoir boundaries and understanding the reservoir structure up to a level etc. All these are used in the field development planning (FDP). Conventionally, in a pressure transient interpretation a reservoir layer is taken as homogenous, i.e., the reservoir properties are taken uniform across the thickness of sand unit. In highly heterogenous reservoirs, this approach may lead to under-estimation or over-estimation of permeabilities, since a homogenous layer doesn't consider the vertical heterogeneity within the layer. Hence, to address the vertical heterogeneity, multi-layer reservoir model is used in pressure transient interpretations. Each of these layers can be treated as a petrophysical facies. This paper discusses various ways of petrophysical facies modeling and showcases the usage of these layered reservoir models in pressure transient interpretations. The results from both conventional as well as multi-layered model are compared in different type of reservoir sands. It is observed that a multi-layer reservoir model gives better results for vertical and horizontal permeabilities in a vertically heterogenous reservoir. The degree of layer division defines the vertical resolution or refinement of permeability values. In a homogenous sand unit, the conventional model can be used up to a certain degree of accuracy.
Deepwater is an extremely cost-intensive exploration frontier representing a high-risk/high-reward scenario. After the world’s largest deepwater gas discovery in on the east coast of India, the area has attracted several operators and activity has picked up considerably in recent years. Currently, five deepwater rigs and drillships are operating in water depths ranging from 1500 m to 3000 m. This cost-intensive scenario dictates the use of techniques which maximize quality information while minimizing rig time. Interval pressure transient testing (IPTT) on wireline and conventional testing acquire essentially the same data and use the same analytical tools. Conventional well testing methods obtain the average properties of multiple layer systems but turn out to be time-consuming and hence expensive, especially if the fluid is only water. However, wireline acquisition is much more appropriate for accessing multiple layers and is far less time consuming; additionally, it can be carried out in open holes as well. The radius of investigation identified by the progressive pressure transient is sufficiently large to determine essential reservoir properties. With IPTT, the evaluation can be made layer-wise, and these evaluations are very critical for both the exploration and appraisal stages of the field development. IPTT has been performed in deepwater wells in India using the dual-packer configuration of wireline formation testers. IPTT is used to evaluate reservoir parameters, capture representative fluid samples, and assess commercial viability and flow potential for multiple reservoir intervals. This potentially eliminates the need for conventional well testing on expensive deepwater rigs, thus significantly reducing operating cost by use of state-of-the-art technology. This paper showcases the workflow and process involved in the impact area of formation evaluation from a reservoir dynamics perspective and use of a calibrated, continuous permeability curve in calculations of full well deliverability in case of gas discovery.
Cloud computing has become the buzz word in the last few years. All the service industries from different fields are using cloud computing based data analytics to optimize their operations in order to improve the customer user experiences and the overall efficiency. It is mainly due to the use of high volume computing backed by significant development in advanced hardware capabilities. This paper describes the ‘what’, ‘why’ and ‘how’ based questions on cloud computing. To start with, a brief introduction of cloud computing has been discussed along with the history of computation usage in oil industry. Followed by that a brief introduction highlighting the significance of Artificial intelligence and machine learning in the current computing environment has been explained. As the industry moves towards more and more usage of digital oilfield techniques, the dominance of high end computing and data analytics in the oil and gas industry is also showcased. Once cloud computing is established as a standard, the paper further discusses different modes of cloud delivery service models- Infrastructure as a service (IaaS), Platform as a service (PaaS) and Software as a Service (SaaS). The paper also identifies the challenges and concerns/issues that comes as a part of cloud computing methodology and then describes how these all challenges are being addresses. This paper elucidates the comprehensive view of the cloud computing landscape in oil and gas arena through a review of available noteworthy open source literature
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