The Deccan Traps large igneous province (LIP) comprises one of the largest continental flood basalt provinces on Earth with the main phase of volcanism spanning the Cretaceous-Palaeogene boundary. The oldest volcanism of the province is encountered in the northwest of modern-day India where Deccan stratigraphy is often buried beneath thick Cenozoic sedimentary sequences. The Raageshwari Deep Gas (RDG) Field, located onshore in the central Barmer Basin, NW India, produces gas from the early Deccan Raageshwari Volcanics which are subdivided into two members, the Agni Member and the overlying Prithvi Member.The RDG comprises a globally important example of a producing volcanic reservoir whilst also offering unique insights into the early volcanism of the Deccan with the aid of extensive high quality sub-surface data. Within this study, the volcanic facies of the RDG sequences are investigated from five cored intervals (total 160 m). Core-based facies determinations are compared with geochemical analyses, petrophysical analyses of the cores (density, porosity and permeability), and wireline data including micro-resistivity borehole images (FMI) and Nuclear Magnetic Resonance (NMR) data. A wireline based volcanic lithofacies scheme is developed and applied to the uncored parts of the sequence which in turn is compared to 3D seismic data. Results of the study reveal the Agni Member to comprise a compositionally bimodal (basalt through to trachyte), dominantly alkaline series with mixed volcanic facies including spectacular felsic ignimbrites, basic-intermediate simple lava flows, volcaniclastic units and newly identified shallow intrusions. The Prithvi Member in contrast is dominated by tholeiitic basalt compositions with less common basic-intermediate alkaline compositions and comprises a sequence dominated by classic tabular lava flow facies inter-digitated with boles, volcaniclastic units, rare compound braided lava facies and evolved tuffaceous ash layers. In one interval of the Prithvi Member, evidence for agglutinated spatter is recorded inferring potential proximity to a palaeo-eruption site within the area. Comparison between core data and volcanic facies reveals a first order control of volcanic facies on reservoir properties

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 Raageshwari Deep Gas (RDG) Field, situated in the southern part of Barmer Basin, is a tight gascondensate reservoir comprising of Volcanics with basic lava flows (basalts) and stacked silicic pyroclastic flows (felsic) interbedded with basalts, and overlying clastic Fatehgarh Formation. The field is currently being developed using deviated wells with multi-stage hydraulic fracturing. The volcanic rocks pose a significant challenge in reservoir zone identification and trend prediction. Variability in mineralogy, lithofacies, thickness of reservoir subunits and areal distributions of pores/vesicles and fractures results in marked reservoir heterogeneity. This paper demonstrates a comprehensive facies characterization for pay zone identification, building a robust reservoir model and execution of multistage hydro-fracturing. The facies characterization methodology integrates cores, mudlogs (gas shows and chromatographs), wireline logs, hydraulic fracturing and production data. Conventional (sand-shale) petrophysical workflows are not applicable to volcanic rocks that are fundamentally different in nature. Hence a new unconventional work flow was established and validated in pilot wells. It was evident that the key parameter to address would be permeability given the tight nature of the formation (micro-pores). An initial facies classification was conceptualized integrating basic suite of logs and core data. New learnings on well performance behavior were assimilated with NMR log data in further refining the facies model. Higher gas counts and higher productivity was found to be associated with higher NMR bins indicative of larger pores and hence better facies. The pay zones identified based on refined facies model helped in optimizing hydraulic fracturing of around 100 zones in 15 wells in recently concluded Hydro-frac campaign. The pin pointing of better producible zones in an approximately 700 m thick volcanic package facilitated reduction in operational costs. Multiple perforations (clusters) were combined in each fracturing stage; injectivity of individual cluster was checked during mini-frac and post fracture temperature analysis resulting in an optimized hydro-frac job. Production logging was carried out to confirm contribution from stimulated intervals. It was observed that almost all fractured intervals were contributing to production validating the petrophysical work. Improved facies classification was also built into the reservoir model thus improving the property distribution and reservoir predictability away from the wellbore. This study facilitated in building a robust history matched reservoir simulation model for realistic production forecasting. This case study from an unconventional volcanic reservoir emphasizes the importance of integrating different datasets, in unraveling reservoir complexity leading to increased confidence in effective reservoir management. The volcanic reservoirs pose a huge technical challenge for sustained production performance and reservoir management; calling for continuous upgrading of the facies model by aggregating data from hydro-fracturing and newly drilled wells.

The Raageshwari Deep Gas Field, Barmer Basin, India is a low permeability, moderate CGR gas condensate reservoir. It is a low net to gross system with gross reservoir thickness varying from 500-1000m. The pay zone consists of a poorly sorted sandstone interval on top of a stacked volcanic succession of thick lava flow cycles. The wells have been completed with multi-stage hydraulic fracture stimulations to allow production at economical rates.The major challenge is to improve fracture placement to achieve wellbore connection with the entire net reservoir storage and flow capacity. Connecting each and every net reservoir packet would increase the number of fracture stages and in turn increase the cost significantly. Thus an optimization workflow was generated to increase the efficiency of hydraulic fracturing and reduce the cost of connecting the maximum net reservoir through hydraulic fractures.An integrated approach including petrophysical and geomechanical analyses was used to identify the potential zones for hydraulic fracturing. Fracturing technologies like limited entry technique using cluster perforation were used to increase the net connected reservoir thickness while employing as few fracture stages as possible. Several post fracturing data acquisition programmes were conducted to estimate fracture parameters such as fracture height, half-length and conductivity to help evaluate the performance of each fracture stage. Single well analytical and numerical models were developed to estimate the impact of connecting maximum net reservoir thickness in terms of both initial production rate (IP) and the expected ultimate recovery (EUR) of the reservoir.The limited entry fracturing technique with cluster perforation used in several wells was helpful in connecting the maximum net reservoir in the thick gross pay sections present. Based on a cost-benefit analysis, the number of fracture stages for each well was optimized with the goal of connecting the maximum net reservoir thickness to the wellbore. The fracture height achieved in each fracture stage was verified through micro-seismic, RST and temperature log measurements and pressure transient analyses.Once the height was ascertained, other parameters were obtained from post-fracturing pressure matches and pressure build up data. The estimated impact of connecting the maximum net reservoir storage and flow capacity as compared with the initial plan of 4-5 conventional single perforation hydraulic fractures is estimated to be production of~5% GIIP in 15 years.