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.

The Raageshwari Deep Gas Field (RDG), Barmer Basin, India, is a thick (~900m gross), low permeability (0.01-1md) gas condensate field (CGR: ~70 STB/MMscf). The pay-zone consists of a poorly sorted sandstone interval on top of stacked succession of volcanic lava flow cycles. The field is being developed through multi-stage hydraulic fracture stimulations to allow production at economical rates. Recently two hydraulic fracturing campaigns comprising of 125 stages in 20 wells were successfully completed which have resulted in significant improvement in well productivity. This paper highlights the integrated workflow applied in a volcanic reservoir to reduce subsurface uncertainty and value addition in optimizing hydraulic fracturing operation. To account for the complexity associated with volcanic rocks, a fit for purpose integrated petrophysical and geomechanical workflow was developed using a basic wireline logs, processed NMR, dipole sonic and image log analysis. The model was calibrated with dynamic data especially diagnostic fracture injection test (DFIT), pressure build up and production logging tool (PLT) analysis. The final calibrated model was used to identify the net reservoir packets along the well length, which further helped to identify the optimum locations to create hydraulic fractures. A typical log motif generated using the integrated model is given in Figure-1. As seen on the generic log in Figure-1, net reservoir intervals are in multiple packets of varying thickness contained throughout the thick gross reservoir package. Connecting maximum net reservoir packets through hydraulic fractures is critical for maximizing the well productivity and EUR. The limited entry fracturing technique (Lagrone and Rasmussen, 1963) was used to connect the maximum net reservoir with a fewer number of stages and a lower cost. Extensive data acquisition (extended DFIT, formation wise testing, PVT sampling, PLT and pressure build-up) was carried out to increase reservoir understanding followed by detailed subsurface modeling. The extensive data acquisition programme was successful in reducing a number of uncertainties, including: reservoir information, effective fracture parameters and presence of natural fractures. The key outcomes from the two frac/data acquisition campaigns are as follows: The integrated petrophysical and geomechanical model enabled us to improve the net connected reservoir by 65% in the volcanic sectionsThe optimisation of the number of frac stages and their costAn improved subsurface understanding in well deliverability, frac conductivity, half-length and frac heightConfirmation of gas contribution from each perforation and the establishment of deeper gas which validated petrophysical payA new, more accurate, poro-perm transform calibrated with permeability estimation using DFIT and pressure build upA better subsurface understanding which supports higher estimates of GIIP and EUR

Raageshwari Deep Gas (RDG) is a clastic-volcanic reservoir located in the southern Barmer basin, India. RDG is a tight retrograde gas-condensate reservoir of permeability in the range of 0.01-1 md with a condensate gas ratio (CGR) of ~65 stb/mmscf. RDG is composed of a poorly sorted sandstone interval (Fatehgarh formation) overlying low net-to-gross (NTG) stacked succession of thick cycles of volcanic units (Basalt and Felsic) of ~700m gross thickness at a depth of 2800 m. RDG field is being developed using pad-drilled deviated wells, with multi-stage hydraulic fractures. In tight gas fields, one of the major challenges is obtaining the right set of parameters to accurately forecast the estimated ultimate recovery (EUR) per well. EUR per well depends on fracture parameters such as fracture half-length (Xf), fracture height (Hf), fracture conductivity (Fc) and reservoir characteristics like matrix porosity (Φ), matrix permeability (k), net pay thickness (h), drainage area, reservoir pressure, reservoir fluid and operating conditions. EUR may be estimated using decline curve analysis (DCA), rate transient analysis (RTA), and reservoir simulation. DCA is the simplest method but has high uncertainty early in a well’s production history, reservoir simulation is complex and requires detailed reservoir characterisation. RTA is easier compared to reservoir simulation and gives reasonable estimations of fracture and reservoir parameters. Since RTA is performance based it provides continuous evolution of high confidence EUR, even with limited production history. To characterize tight fields, estimating kh of various layers through pressure transient analysis (PTA) requires long shut-in data. Thus PTA is generally only available for analysing early time effects (like fracture parameters). Thus, in low permeability reservoirs, RTA becomes preferred tool since it does not require shut-in data. RTA models and type curves generate non-unique solutions. Hence, integrating the petrophysical database with production logs, PTA results and RTA results is utilized to reduce uncertainty in k, h, Fc, and Xf. By utilizing all these data, the uncertainty in EUR estimation per well is reduced. These parameters are used as input for history matching to validate the interpretation and to optimize the RTA solutions. It was observed that history matches in RTA were improved when Fc and Xf from PTA were available. Flowing material balance (FMB) was then used to estimate drainage area, GIIP and EUR per well. This paper demonstrates the workflow to use PTA, RTA, production logs, and petrophysical data to obtain the right set of parameters to get high confidence in EUR per well. The finalized EUR per well for different well types can then be used for field development and deciding well spacing. Full field production forecasting based on RTA provides additional validation or an alternative to the estimates done through reservoir simulation.

Raageshwari Deep Gas field situated in southern Barmer Basin of India is a retrograde gas condensate volcanic reservoir. More than 150 fracturing treatments have been pumped in this reservoir to achieve sustained economical production. The paper describes the results of a statistical analysis done to find correlations between production data and fracturing design parameters including petrophysical and geo-mechanical properties of the rock, pre-frac diagnostic tests, and fracturing treatment data including both pumping data and pressure matched parameters. This paper uses the data from multiple production logs to generate stage wise Productivity Index (PI). This PI data was then cross plotted against various parameters and combinations of parameters such as In-situ proppant concentration, formation porosity, net pay, average stress, proppant mass pumped per stage, fracturing fluid recovery rate and percentage, and fracture dimensions. One interesting line of investigation looked at the rate of pressure decline post Step Rate Test (SRT). A method was developed to evaluate the SRT declines even though they were too short to analyze for permeability using post closure analysis. This paper presents the results of these statistical analysis and where reasonable correlations were obtained. It also shows that for this volcanic formation, the rate of pressure decline after the SRT is a better indicator of Reservoir Quality (RQ) and future stage performance than the log derived porosity and permeability. While the use of short term fall-off data is only qualitative, it does appear to be an effective tool for evaluating the potential of a stage just before fracturing which would allow improved onsite treatment optimization. Since the quality of a reservoir generally varies across the areal extent of a field, it is very important to ascertain the same either qualitatively or quantitatively. This paper presents a technique for qualitatively defining RQ, which can be useful to validate the pre-existing workflows used for defining RQ.

The Raageshwari Deep Gas (RDG) field, situated within Barmer Basin in the State of Rajasthan, India, was discovered in 2003. The field is a tight gas condensate reservoir, with excellent gas quality of approximately 80% methane, low CO2 and no H2S. Since the permeability (0.01 - 1 md) is low in this reservoir, hydraulic fracturing is required to get substantial recovery from the wells. The field has been under production since 2010. The development of this field has been carried out in three phases and more than 150 fracturing treatments have been pumped in this reservoir till date to achieve sustained economical production. This paper deals with the lessons learnt and changes implemented in choke design through various development phases of the field. In the initial phase of field development, chokes with a low Flow Coefficient (Cv) were installed to meet the requirement of controlling the wells at low flow rates and high differential pressure. Later as the surface handling capacity increased, the chokes had to be de-bottlenecked, requiring additional Capex for new chokes. To avoid a similar scenario in the future, a comprehensive approach has been followed to envisage Cv requirement, considering well wise production profiles and surface handling capacities throughout the life of field. Since a single trim can't operate over the complete life-cycle of a well, trim interchangeability has been included in the choke design such that low and high Cv trims are interchangeable. Pre-mature failures of trims were observed in initial phase and a root cause analysis was done to ascertain the reason. Based on the analysis, trim metallurgy has been changed from Tungsten Carbide to ASTM A276 Specific Stainless Steel Grade 440C. Trims with newly selected mettalurgy have been installed in the existing chokes. The introduction of trim interchangeability has saved MMUSD 0.3 in the future Opex as the requirement of procuring altogether new chokes for late life period of wells is avoided. Initially failures in the trim bodies were observed as early as two months of commissioning but with the change in metallurgy zero failures have been observed with operational life of chokes being higher than four years. This has avoided significant downtime on wells and expenditure on regular trim changeovers. Although Tungsten Carbide is one of the most common materials used for constructing trims world over, there could be specific cases where-in other metallurgy may add better value. The workflow followed in this paper will help select a suitable metallurgy and can impart a significant value to the industry.