Digital core generated from micro CT images of rock sample cutting and results obtained from digital core analysis are presented in this work as a substitute of conventional core study for Petrophysical evaluation. Conventional core extraction during drilling, core preservation and analysis are expensive, time consuming processes and often unavailable for small size fields. Moreover, routine and special core analysis results are a critical input for petrophysical characterization. In this situation, digital core study appears to be a cost effective substitute to ensure and validate petrophysical evaluation results. High resolution 3D micro CT imaging and analysis was done on rock samples cut during drilling or on sidewall core plugs cut by wireline logging tool. Segmented micro CT image slices when combined in 3D space in three orthogonal directions, can be termed as digital core. Solid rock matrix, clay filled and porous rock portions are distinctly separable using micro CT images and their volume fractions can be estimated. Detail textural analysis in terms of Grain and pore throat size distribution of the rock is possible from digital core which controls storage capacity and flow behavior. Two critical petrophysical input parameters for fluid saturation (Sw) estimation are cementation exponent (m) and saturation exponent (n). These parameters are commonly computed from special core analysis (SCAL) on conventional core plugs. But digital core study can provide the estimates of ‘m’ and ‘n’ which replace the need of SCAL. Digital core study has been carried out in three different reservoirs in west and east coast of India and the results were analyzed. Porosity and permeability data obtained from digital core was first compared with log analysis results and then used to identify different petro physical rock types (PRT). Fluid saturation (Sw) was estimated from resistivity log by using ‘m’ and ‘n’ exponent obtained from digital core seems to be more realistic and corroborates with well test results. Porosity, permeability, water saturation and rock types (PRT) were helped to build geo-cellular model (GCM) for small and marginal reservoir. Enhanced reservoir characterization by using digital core study result has helped in better understanding and decision making for small and marginal fields where limited well data is available. Finally this leads to the preparation of field development plan (FDP). Digital core technique is less expensive, having quick turnaround time than conventional coring which has translated into high value business impact for any development project.

Effective sand control is extremely important for production of hydrocarbons from shallow unconsolidated sand reservoir. In absence of any sand control measure installed in the well, there is high risk of Sand production along with the hydrocarbons. Sand production may result in damage of X-Mass tree and/or Sub-sea infrastructure components. In extreme cases, when the sand production goes beyond the critical limit, it may lead to a situation when the field production has to be stopped. In view of this, in Deep water environment, sand production is considered as a potential hazard. It may lead to tremendous impact on reservoir economics and sustained production from the field.

Initial water saturation (Swi) in a gas reservoir is an important parameter for inplace resource (GIIP) and ultimate reserve estimation, which in turn impacts the economic decision. Swi estimation in a low resistivity deep-water clastic reservoir is more challenging because limited well data in less number of (costly) appraisal wells in a large area. Conventionally, Swi is computed from open hole logs and validated with core plug data to reduce the range of uncertainty in estimation. But this standard methodology fails when resistivity log derived Swi shows a variance with the saturation measured from the core plugs and increases the range of uncertainty. Sometimes, log derived Swi shows high water saturation in the gas bearing interval due to low anomalous resistivity which is beyond correction. Saturation height modelling is an age old solution for this sort of problem and the same was attempted first to estimate Swi. But single saturation height function does not represent all the rock types of the reservoir and replicate log derived Swe curve. Petrophysical rock typing was carried out using porosity and permeability from the core plug in the first step and then by using the concept of flow zone index (FZI) and rock quality index (RQI). FZI-RQI based rock types were able to characterize the reservoir in a better way in 3D-Geologic model and also able to separate the different behaviours of Capillary pressure curves.Two saturation height functions were made after characterizing good rock and poor rock type, which were tested in the dynamic model for flow simulation and recovery factor estimation successfully. This innovative concept of FZI-RQI based petrophysical rock typing (PRT) and saturation height modelling finally added value to recreate the Swi curve against the low resistivity pay interval and to reduce the range of uncertainty in Sw estimation.