Formation testing has been widely prevalent in the industry for critical information, such as reservoir pressure, gradient analysis, and fluid identification, that aids formation evaluation. This paper focuses on the successful evaluation of low-mobility reservoirs using the 3D radial probe as compared to the conventional probe in a comprehensive study of 60 wells (most of them offshore) across India. One of the major challenges in formation evaluation, fluid flow from any interval is not certain. Prospective zones are encountered that lie in unconsolidated sands where critical drawdown pressure cannot be exceeded because of formation integrity issues or there are zones that have low mobility and thus cannot be tested. Reliable pressure results cannot be obtained from these formations, nor can the fluids in these zones be identified because of poor flow potential. To overcome this major challenge, different probe (tool inlet) configurations are used that increase the flow area and help test tight formations (e.g., the 3D radial probe). In this study, 1754 stations were analyzed across several heterogeneous formation types and multiple operators to verify the diverse applicability of the 3D radial probe. The analysis was conducted in two phases. Formation testing results from the first phase showed that 47% and 68% of the points of interest in 2018 and Q1, Q2 of 2019, respectively, across all wells remained unevaluated with the conventional probe. Even among the points that gave valid results, there were low-mobility points where downhole fluid analysis (DFA) was not possible because of poor flow potential. Upon introducing the 3D radial probe in six wells, the shortfall of the conventional probe was overcome, which ultimately contributed to 35% additional evaluation success in 2018. In a comparison of the performance on the same wells and same formations, 3D radial probe fluid identification success in 2019 was 93% compared to 2% success in conventional probe evaluation in these tight reservoirs. Through this study, the uncertainty of fluid typing in the tight reservoir was resolved. Accurate interval permeability values were determined and were input to well deliverability estimates. The 3D radial probe results also help the drillstem test (DST) design, saving significant well cost because wet intervals are avoided using downhole fluid characterization, which revolutionizes formation testing in tight reservoirs.
The present oil industry is more challenged than ever to develop novel methods for oil exploration and production, while reducing costs at the same time. This necessity changes the need of logging tools for reservoir characterization. Saturation height modeling (SHM) is an important aspect of determining the production capability of an oilfield. This is often performed by taking core samples, which is pivotal for such analysis, but expensive and challenging. Further, cores are usually taken in the zones of interests in the well. This calls for an alternate analysis, which is not only available for the entire interval of the well but is also less expensive than the traditional coring techniques. Nuclear Magnetic Resonance (NMR) applications have proved promising over the years to perform SHM, without using cores. NMR, however, has a shallow depth of investigation and using wireline measurements is even more challenging due to longer time after bit and increased mud filtrate invasion. Consequently, its use is restricted to quantifying porosity. This makes it imperative to remove the effect of any filtrate or hydrocarbons from NMR logs to be able to use them for any advance analysis. A novel methodology is presented in this paper to perform SHM analysis in carbonates. It uses NMR data along with modern processing techniques like factor analysis (Jain et al. 2013) and fluid substitution (Minh et al. 2016) and integrated workflow to define hydrocarbon uncontaminated pseudo capillary pressure curves and saturation height functions for different rock facies observed in the formation. The results are validated on five wells in the same field, and further confirmation is also done with testing results.
Deep wells drilled down to 4000 m to 4500 m true vertical depth (TVD) in the offshore Kutch-Saurashtra rift basin encounter more than 1500 m of abrasive Deccan Trap volcanics in a 12.25-in. section with target stiff Mesozoic sandstone formations in an 8.5-in. section. Weathered basalt flows, fractured sandstones, tightly cemented siltstones, pyritic shales, abnormal pressures, and complicated transverse isotropic layers test the limits of well construction and engineering design at high-pressure, high-temperature (HPHT) conditions. This reduces the rate of penetration (ROP) and sidetracks with premature termination of wells. Traditional prognosis methods fail to predict the abnormal pore pressure regimes and stress anisotropy created by the disturbed tectonic history and complex geological setting. The operator faced unpredictable flow events and wellbore instability incidents such as cavings, tight pulls, breakouts, and equivalent circulating density fluctuations during drilling. Apart from the drilling and completions challenges, the wellbore instabilities affected openhole logging and coring operations, leading to inadequate formation evaluation. In this paper we present an integrated approach to using geomechanical analyses for determining the mud-weight window, drilling bottomhole assembly (BHA), and optimizing mud chemicals. An anisotropic Mechanical Earth Model (MEM) was built using both horizontal and vertical elastic properties to estimate an accurate stress profile that can guide mud loss zones and completion quality. Engineered drilling bits based on the estimated rock mechanical and stress analysis were selected to improve effective ROP through the more abrasive and compacted rocks. High risk zones were flagged inside the Deccan Trap for mud loss while look-ahead mud weight design for the Bhuj and Jhuran formations were optimized by considering plane of weakness mode of failure. Dynamic hydraulics simulation was conducted for the tripping speed of the Casing and BHA. The casing run-in speed was optimized across the Deccan Trap by pumping lost-circulation material (LCM) additives to mitigate losses. This helped to set casing until the 12.25-in. section at total depth (TD) with a narrow mud-weight window of 0.2 to 0.3 ppg. A mud weight of 12.7 to 13.0 ppg was used initially in the 8.5-in. section based on the look-ahead model and was proactively increased to 13.7 ppg to minimize nonproductive time (NPT) with very few borehole breakouts or fracture plane slippage. This result was quite different from offset wells that were drilled with only 11.5 to 12.2 ppg mud weight, which resulted in many tight-hole and stuck-pipe incidents. Bits were changed to manage mean stress, which was expected in the range of 15,000 to 17,500 psi, with formation strength ranging 9,500 to 23,000 psi. The 8.5-in. section was drilled successfully with fewer bit trips, and the hole condition was in better shape compared to the offset wells. The formation evaluation and completion quality review led to the successful discovery of four new zones with minimal near-wellbore damage. Despite the extreme conditions, there was improvement in the instantaneous ROP by 15 to 20% while drilling an additional 250 m of abrasive formation without any wellbore instability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.