No abstract

No abstract

A new iterative modelling workflow has been designed to reduce uncertainty of water saturation (Sw) calculations in the tight Barik sandstone in the Sultanate of Oman. Results from this case study indicate that Sw can be overestimated by up-to twenty saturation units if the as-acquired deep resistivity is used in volumetric calculations. Overbalanced drilling causes deep invasion of water-based mud (WBM) filtrate into porous and permeable rocks, leading to radial displacement of in-situ saturating fluids away from the wellbore. In low-porosity reservoirs drilled with WBM the inability of the filtration process to quickly build impermeable mudcake translates into long radial transition zones. Under certain reservoir and drilling conditions, deep resistivity logs cannot reliably measure true formation resistivity and are therefore unable to provide an accurate assessment of hydrocarbon saturation. The effect of mud-filtrate invasion on resistivity logs has been extensively documented; processing techniques utilize resistivity inversion and tool-specific forward modeling to provide uninvaded formation resistivity logs which are much better suited for in-place resource volume assessment. However, sensitivity analysis shows that the accuracy of invasion-corrected logs dramatically decreases as the depth of invasion increases whereby the inversion process needs to be further constrained. The new workflow is designed to reduce the non-uniqueness of true formation resistivity models, so that they honor multiple and independent petrophysical data. The inversion routine utilizes a Bayesian algorithm coupled with Markov-Chain Monte Carlo (MCMC) sampling. Inversion results are iteratively modified based upon two rock property models: one derived from rock-core data (helium expansion porosity and Dean- Stark saturations), and the other using an equivalent log interpretation of thick reservoir intervals from oil-based mud (OBM) wells. Simulated borehole-resistivity are compared to field logs after each validation loop against rock property models. The new inversion-based workflow is extensively tested in the unconventional tight Barik formation across water-free hydrocarbon and perched water intervals and inversion-derived Sw models are independently validated by capillary pressure-derived saturation-height models and fluid inflow rate from production logs.

The process of mud-filtrate invasion involves immiscible fluid displacement and salt mixing between mud-filtrate and formation fluids in porous and permeable rocks. Consequently, the post-invasion spatial distribution of fluids and electrolyte concentration around the borehole affects resistivity measurements with different depths of investigation (DOI). In the presence of deep mud-filtrate invasion, the assessment of water saturation in the uninvaded zone based on the deep resistivity log can be inaccurate. Deep and electrically conductive filtrate invasion coupled with shoulder-bed effects can artificially increase water saturation (Sw) estimations by 20 saturation units (s.u.) in the Barik reservoir, resulting The process of mud-filtrate invasion involves immiscible fluid displacement and salt mixing between mud-filtrate and formation fluids in porous and permeable rocks. Consequently, the post-invasion spatial distribution of fluids and electrolyte concentration around the borehole affects resistivity measurements with different depths of investigation (DOI). In the presence of deep mud-filtrate invasion, the assessment of water saturation in the uninvaded zone based on the deep resistivity log can be inaccurate. Deep and electrically conductive filtrate invasion coupled with shoulder-bed effects can artificially increase water saturation (Sw) estimations by 20 saturation units (s.u.) in the Barik reservoir, resulting in pessimistic estimates of hydrocarbon pore volume if no corrections are applied. The Barik sandstone reservoir, which is characterized by low porosity (up to 14pu), low-to-medium permeability (up to 40mD) and high residual gas saturation (40 to 50%), exhibits low storage capacity to admit the critical filtrate volume necessary for building an impermeable mudcake. Combined with multiple days of overbalanced exposure to saline water-based mud (WBM), mudfiltrate invasion results in deep and smooth radial transition zones where the uninvaded formation is far beyond the depth of investigation of laterolog tools. Deep resistivity values are therefore lower than the true formation resistivity. Additionally, numerical simulations of resistivity logs show that the resistivity reduction by conductive invasion is further aggravated by shoulder-bed effects when individual reservoir thickness falls below 2.5 meters. This paper describes the implementation of a compositional fluid-flow simulator to numerically model WBM-filtrate invasion and mudcake buildup in vertical boreholes. The algorithm allows the simulation of physical dispersion and fluid displacement around the borehole in a multi-layer model. Time-dependent radial profiles of Sw and salinity are combined with corecalibrated porosity and electrical properties to compute electrical resistivity via Archie’s formulation. Subsequently, numerically simulated logs are generated using vendor-specific forward model processing and compared against field measurements. This workflow was extensively tested in various reservoir intervals with a wide range of petrophysical rock types and drilling conditions. Results show that the deep laterolog exhibits low sensitivity to conductive filtrate invasion when reservoirs porosities are lower than 8%. Above that threshold value, invasion length is a non-trivial process involving multiple variables. Even though exposure time to open-hole conditions is a key factor leading to deep invasion, certain reservoir characteristics can lead to deeper invasion at short exposure times and significantly increasing uncorrected Sw estimates.

An accurate Mechanical Earth Model (MEM) is of vital importance in tight gas reservoirs where hydraulic fracturing is the only way to produce hydrocarbons economically. The Barik tight gas reservoir is the main target in Khazzan and Ghazeer Fields at the Sultanate of Oman (Rylance et al., 2011). This reservoir consists of multiple low-permeability sandstone layers interbedded with marine shales. A good understanding of the fracture propagation in such a reservoir has a major effect on completion and fracturing design. The MEM derived from sonic logs and calibrated with core data needs to be further validated by independent measurements of the fracturing geometry. Multiple surveillance techniques have been implemented in the Barik reservoir to validate the MEM and to match observations from hydraulic fracturing operations. These techniques include closure interpretation using a wireline deployed formation testing assembly, the use of mini-frac injection tests with deployed bottomhole pressure gauges, execution of post injection time-lapse temperature logging, the injection of radioactive tracers, associated production logging, subsequent pressure transient analysis and other techniques. A cross-disciplinary team worked with multiple sources of data to calibrate the MEM with the purpose of delivering a high-confidence prediction of the created fracture geometry, which honors all available surveillance data. In turn, this validation approach provided a solid basis for optimization of the completion and fracturing design, in order to optimally exploit this challenging reservoir and maximize the economic returns being delivered. For example, combination of stress testing with radioactive tracers provided confidence in stress barriers in this multilayered reservoir. Pressure transient analysis allowed to calibrate mechanical model to match fracturing half-length that is contributing to production. This paper provides extensive surveillance examples and workflows for data analysis. Surveillance of this degree in the same well is uncommon because of the associated time and cost. However, it provides unique value for understanding the target reservoir. This paper demonstrates the Value Of Information (VOI) that can be associated with such surveillance and provides a concrete and practical example that can be used for the justification of future surveillance programs associated with the hydraulic fracturing operations.