The Raageshwari Deep Gas Field is situated in the southern part of the onshore Barmer Basin in Rajasthan, India. The field contains gas condensate with excellent gas quality reservoired dominantly within the tight volcanic rocks. Optimal development and production of the tight reservoirs requires characterization of faults and natural fractures that are important to fluid flow and production. Reservoir quality of the volcanic complex is governed by the distribution of matrix pore spaces and fractures. Use of seismic attributes for detecting effective reservoir pore spaces such as fractured zones and vesicles is challenging considering the limits of seismic resolution in the tight volcanic reservoirs. Poststack seismic attributes used in this study for fracture detection include geometric attributes such as coherency for detection of seismically resolved faults and reflection curvature attributes for discrimination of subseismic faults. Discrete frequency components extracted from seismic data are also used to analyze geologic discontinuities. Besides geometric attributes, seismic wave attenuation from the basic instantaneous seismic attributes — instantaneous amplitude, phase, and frequency — are also key indicators of fractured zones and vesicles that create effective pore spaces. In fractured intervals within the volcanic reservoirs, a decrease in density and slowdown in acoustic propagation velocity yields a relative drop in P-wave impedance, which are important characteristics to determine fractured zones. Detected fractured zones from seismic attributes were validated with wells, image logs, and production data. In addition to fracture detection, predicting subsurface properties, such as porosity distribution away from wells, has always been a fundamental requisite for appropriate infill well planning. Full-azimuth seismic data and selected seismic attributes were used in multiattribute analysis to predict porosity and were correlated with “blind” wells. This study captures the heterogeneous volcanic rock porosity distribution in the field, improving the understanding of varied production behavior observed within the volcanic rock complex.
Raageshwari Deep Gas (RDG) Field in the Southern part of Barmer Basin is a tight gas-condensate reservoir composed of a thick volcanic unit overlain by volcanogenically-derived clastic Fatehgarh formation. This tight reservoir hosts significant gas reserves and is being successfully exploited with the implementation of multi-stage hydraulic fracturing. For optimum hydraulic fracture stimulation, a clear understanding of the geomechanical properties of the reservoir and its seamless integration with petrophysical interpretation is of paramount importance to achieving long-term sustainable well performance. The key geomechanical factors in hydraulic fracturing of deep volcanic reservoirs form a niche subject as opposed to the widely published unconventional shale plays. This paper illustrates the workflow developed for construction of 1D-Geomechanical model in tight volcanics and its application for selecting perforation intervals and designing of frac jobs; its validation through diagnostic fluid injection, execution of hydraulic fracturing jobs and associated challenges. The one dimensional Geomechanical model integrates basic petrophysical logs, dipole sonic data, rock mechanical tests on core, processed image log data with break out analysis, regional tectonic history, existing natural fracture evidences and drilling data. Most importantly, the model is calibrated with field test data such as diagnostic fluid injectivity test (DFIT), step rate test (SRT) and mini-frac data. The workflow involves estimation of rock mechanical properties (Young's modulus, Poisson's ratio, uniaxial compressive strength) based on logs and calibration with core data and documented analogues. The next step is modelling of stresses in the field for identification of current stress regime. Integration of failure models with wellbore image data provides the understanding of maximum horizontal stress. Basic log data is used for estimation of over burden and pore pressure. Calibration of pore pressure is carried out from the DFIT data. The third step involves the assimilation of rock strength model with stress model to estimate minimum horizontal stress. In a geologically complex setting with multiple histories of tilting and faulting, tectonics plays an important role in the existing stresses. All these variables are captured and validated with field test data to construct a useful geomechanical model. As part of the recently concluded hydraulic-fracturing campaign, the 1D-Geomechanical model was successfully applied to identify approximately 125 fracture stages in 20 wells for multi-cluster hydro-fracturing in the field. An effective geomechanical model, along with petrophysical interpretation has proved to be helpful in enhancing recovery, improving frac success rate and ultimately, reducing cost on operations. The approach emphasizes the importance of continuous update of the model to deal with variation within the field area and heterogeneity in volcanic rocks.
The current study area, Raageshwari Deep Gas field is situated in the southern part of onshore Barmer Basin in Rajasthan, India. The field contains a gas condensate reservoir with excellent gas quality within the dominantly volcanic formations (Basalt and Felsic) and overlying clastic Fatehgarh Formation. These are tight reservoirs and optimal field development necessitates reasonable characterization of faults and natural fractures thereby aiding well placement by targeting areas of enhanced permeability for better well performance. The minor faults with throws significantly less than the duration of the seismic wavelet may not be detected in variance attribute data. However, reflection curvature is an attribute that also relates to structural deformation and shows greater spatial resolution. The detailed structural lineaments revealed through this analysis are indicative of sub-seismic faults and possible increased intensity of natural fractures. The maximum and minimum curvature data help to accentuate small scale reflection geometry changes and can be used to interpret minor faults. To discriminate stratigraphic features and identify fracture zones, careful calibration was done with production data, image logs and microseismic measurements from the wells. The curvature attributes highlighted lineament distributions, interpreted to be small scale faults and subtle structural deformations associated with fractures. Lineaments of fault/fracture from curvature attributes were observed to correlate with interpretations from borehole image logs. Detected subtle faults were further validated with other measurements like microseismic and production data. These well calibrations provide confidence in the use of specialized seismic attributes for fracture characterization in the field. Results of this study will be used for optimal placement of infill wells for enhanced field productivity.
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