Uncertainty Mitigation Using Data Acquisition in Volcanic Reservoirs

Abstract

Abstract 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