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Gamma ray logging

Gamma ray logging is a geophysical that measures the natural gamma radiation emitted by radioactive isotopes, primarily , , and series, within rock formations to characterize , , and depositional environments in or drill holes. This passive method employs detectors, such as sodium-iodide crystals, to detect gamma rays that penetrate borehole fluids and casing, providing a continuous record of radioactivity levels typically expressed in (API) units. The distinguishes shales, which exhibit high gamma counts due to concentrated clay minerals and , from cleaner formations like sandstones or limestones with lower readings, enabling rapid correlation between wells without direct core sampling. Developed in the late for stratigraphic correlation in petroleum exploration, gamma ray logging gained prominence during for uranium prospecting and has since evolved with advancements in detector technology from early Geiger-Mueller counters to modern tools that differentiate contributions from individual isotopes. Calibration standards, established by the in a test pit at the using concrete mixtures doped with known radioactive concentrations, ensure consistent measurements where 200 API units represent the standard differential in flux between low- and high-radioactivity calibration zones. gamma ray variants further quantify , , and concentrations, aiding in mineralogical analysis, such as identifying clay types via thorium-to- ratios or detecting organic-rich zones through elevated levels under anoxic conditions. In and , logs are essential for estimating volume using indices like the linear Index (V_sh = I_GR), evaluating quality, and mapping paleoenvironments, such as distinguishing fluvial from deposits based on log patterns. Applications extend to , where logs detect contamination plumes or assess , and to resource exploration for phosphates or deposits by correlating radioactivity with mineral grades. Despite influences from conditions like mud weight or casing thickness, corrections via charts maintain accuracy, making logging a foundational tool in subsurface interpretation across open and cased holes.

Fundamentals

Definition and Principles

Gamma ray logging is a geophysical technique employed in to measure the natural emitted by radioactive isotopes within rock formations, enabling the inference of and . This method can be conducted using wireline tools lowered into the or as part of logging-while-drilling operations, where sensors are integrated into the to provide during . The primary utility lies in distinguishing between shale-rich and cleaner formations, as gamma ray intensity correlates with the concentration of radioactive elements. At its core, gamma ray logging relies on the detection of high-energy electromagnetic radiation, known as gamma rays, produced during the radioactive decay of specific isotopes prevalent in geological materials. The key contributors are potassium-40 (K-40), which decays via beta emission followed by gamma emission, and the decay series of thorium-232 (Th-232) and uranium-238 (U-238), which release multiple gamma rays at characteristic energies. These gamma rays interact with the surrounding rock matrix primarily through three mechanisms: photoelectric absorption, where a gamma ray is fully absorbed by an atomic electron, ejecting it and characteristic X-rays; Compton scattering, in which the gamma ray collides with an electron, transferring partial energy and deflecting; and pair production, occurring at higher energies (>1.02 MeV) where the gamma ray converts into an electron-positron pair near a nucleus. In logging tools, scintillation detectors capture these interactions indirectly by recording the resulting scintillation light from ionized materials, converting it to electrical pulses proportional to the incident gamma ray flux. Rock formations exhibit varying radioactivity based on their and , with and clays typically displaying elevated levels due to the adsorption and incorporation of radioactive elements onto surfaces during . is inherent in clay lattice structures like , while and associate with or heavy minerals concentrated in fine-grained sediments; in contrast, sandstones and carbonates generally exhibit lower radioactivity, as and lack significant radioactive content and do not adsorb these isotopes effectively. This differential concentration allows logs to serve as a proxy for shale volume and clay content, aiding in the identification of permeable rocks versus impermeable . To standardize measurements across tools and operators, gamma ray data are reported in American Petroleum Institute (API) units, defined as one two-hundredth of the difference in log deflection between the low- and high-radioactivity zones in the API calibration pit at the University of Houston, where the high zone has radioactivity equivalent to that of the Pierre Shale and the low zone represents typical clean formations. This empirical scale ensures comparability, with typical shale readings around 100-150 API units and clean sandstones below 25 API units, though actual values depend on local geology.

Historical Development

The development of gamma ray logging originated in the late 1930s, driven by the need for a method to evaluate subsurface formations through steel casing, where electrical logs were ineffective. In 1939, Lynn G. Howell and Alex Frosch published the first description of a practical gamma ray well-logging system, utilizing an ionization chamber to detect and record natural gamma radiation from formations in a continuous profiling manner. This innovation, initially tested in boreholes, allowed for correlation between cased and open holes by measuring radioactivity levels, which are higher in shales due to potassium, thorium, and uranium content. Well Surveys Inc. (later Lane-Wells) introduced the first commercial gamma ray log that same year, marking the initial application of nuclear properties in borehole logging for lithology identification and depth correlation. Following , gamma ray logging saw widespread commercialization in the 1940s by major service companies, including and Dresser Atlas, which integrated it into routine well evaluation programs. Early tools relied on Geiger-Mueller counters or ionization chambers, but these had limitations in sensitivity and energy resolution. A significant advancement occurred in the 1950s with the adoption of detectors, such as thallium-activated crystals, which replaced the less efficient Geiger-Mueller counters and provided higher counting rates and better discrimination of gamma energies. This shift improved log quality and enabled more reliable shale identification and formation evaluation in diverse drilling environments. Standardization efforts culminated in 1959 when the () established the Calibration Facility at the , defining the gamma ray unit as one two-hundredth of the difference in log deflection between the low- and high-radioactivity zones in the API calibration pit, with the full difference standardized at 200 units. This unit became the industry standard for calibrating gamma ray tools, ensuring comparability across different instruments and operators. In the late , logging was integrated into logging-while-drilling (LWD) systems, allowing real-time measurements during drilling operations to guide decisions on trajectory and formation evaluation without additional rig time. The brought digital processing advancements, with tools incorporating multichannel analyzers for spectral gamma ray data and computer-based corrections for effects, enhancing accuracy in complex lithologies. Post-2000 developments focused on high-temperature adaptations for high-pressure, high-temperature (HPHT) wells and geothermal applications, including slim-hole LWD spectral gamma ray tools capable of operating up to 200°C with improved and radiation-hardened components. These enhancements, tested in field applications since the , support advanced geochemical analysis and in extreme environments.

Instrumentation and Measurement

Detectors and Tools

Gamma ray logging detectors primarily utilize scintillation crystals to capture incoming gamma radiation. Sodium iodide doped with thallium (NaI(Tl)) crystals serve as the standard primary sensors, converting gamma ray interactions into visible light pulses through scintillation processes. These light pulses are then amplified by photomultiplier tubes (PMTs), which multiply the electrons generated from the light to produce measurable electrical signals proportional to the gamma ray energy and intensity. PMTs are optically coupled to the crystals and housed within rugged, pressure-resistant casings to withstand downhole conditions. Tool designs for gamma ray logging vary based on deployment method and borehole constraints, typically featuring cylindrical sondes for wireline operations. Centralized sondes position the detector symmetrically in the using bow springs or centralizers to ensure uniform exposure to formation , while eccentric designs offset the tool toward one side for integration with pad-based sensors like tools. Standard wireline tools have diameters ranging from 1.5 to 3.5 inches (3.8 to 8.9 cm) and lengths of 2 to 5 meters, allowing compatibility with most sizes while maintaining sensitivity to natural gamma emissions. housings incorporate minimal shielding, often using or materials, to reduce interference from borehole fluids and enhance focus on formation signals without excessive attenuation. Calibration of gamma ray logging tools follows standardized procedures to ensure accuracy and comparability across instruments. The (API) test pits at the provide the primary reference, consisting of concrete blocks with precisely known concentrations of radioactive elements like , , and to define the API gamma ray unit (1/200th of the difference between high- and low-radioactivity standards). Cesium-137 sources are commonly used for detector response verification, emitting monoenergetic gamma rays at 662 keV to simulate formation signals and check linearity. Field corrections account for tool standoff (distance from borehole wall), which can attenuate signals due to mud invasion, and casing effects, where attenuates gamma rays by up to 50% depending on thickness; these are applied using empirical charts or modeling to normalize readings. In logging-while-drilling (LWD) applications, detectors are adapted into compact modules integrated into drill collars for measurements during . These detectors, often using smaller NaI(Tl) crystals (1-2 inches in size) paired with PMTs, are designed to fit within 6- to 8-inch diameter collars and withstand extreme vibrations up to 20g and exceeding 1000g, as encountered in high-rate rotary steerable systems. Advancements through 2025 include enhanced mounting with viscoelastic dampers and reinforced crystal encapsulation to maintain signal integrity under prolonged vibration, enabling reliable correlation at speeds over 100 ft/hr.

Data Acquisition Process

Gamma ray logging data acquisition begins with the deployment of specialized tools into the , primarily through two methods: wireline logging and (LWD). Wireline logging involves lowering a sonde containing the detector via electrical cabling after operations are complete, allowing for high-resolution measurements at controlled speeds typically ranging from 400 to 600 feet per hour (approximately 7 to 10 feet per minute) to ensure accurate capture of natural radioactivity variations. In contrast, LWD integrates the sensor directly into the bottom-hole assembly during active , enabling real-time data collection as the advances, though this method often experiences higher levels due to vibrations and mud flow compared to the stationary post-drilling approach of wireline. The measurement sequence typically proceeds in upward passes for wireline operations to minimize cable drag effects and improve tool centralization, while downward passes may be used in LWD to align with drilling progress; multiple passes can be performed for verification in complex boreholes. Sampling rates vary based on resolution needs, commonly set at 1 to 10 samples per foot, with higher rates (up to 120 samples per foot in advanced systems) employed for detailed profiling of thin beds or high-variability formations. Depth correlation is achieved by integrating a casing collar locator (CCL) tool, which detects magnetic anomalies at casing joints to align gamma ray measurements with pre-existing well records or open-hole logs, ensuring precise stratigraphic tying with errors typically under 0.5 feet. Environmental corrections are essential to account for borehole conditions that attenuate or alter gamma ray signals. Adjustments are applied for borehole fluid and , which can increase —particularly in high-salinity brines containing chlorides that enhance photoelectric effects—using empirical factors derived from tool response modeling; corrections address detector drops at elevated downhole conditions, often exceeding 150°C in deep wells. Casing introduces significant , with casings typically causing 20-50% signal loss due to and photoelectric , necessitating multiplicative correction charts scaled to casing thickness and borehole diameter for accurate formation radioactivity representation. Quality control during acquisition involves real-time monitoring of tool parameters to detect issues such as , where off-center positioning in the can skew readings in enlarged sections, and from electronic interference or statistical counting variations, often mitigated by on-site software alerting operators to anomalies. Post-acquisition, digital filtering techniques remove high-frequency while preserving vertical , ensuring for subsequent analysis through spectral smoothing and outlier rejection protocols.

Types of Gamma Ray Logging

Conventional Gamma Ray Logging

Conventional gamma ray logging measures the total number of gamma rays emitted by rock formations surrounding a across an energy spectrum of approximately 0.1 to 3 MeV, without energy discrimination, to assess overall natural radioactivity. This total-count approach relies on the natural decay of isotopes such as , , and members of the series, providing a simple indicator of content and lithologic variations. The resulting data are output in American Petroleum Institute (API) units, standardized for consistency across tools and environments. The logging tool typically incorporates a single-crystal detector, most commonly thallium-activated (NaI(Tl)), which converts incoming gamma rays into visible light flashes for electronic counting of bulk events. This detector setup offers a vertical of about 2 to 3 feet, constrained by the crystal dimensions, logging speed, and data smoothing parameters that balance statistical with bed boundary definition. Calibration of conventional gamma ray tools occurs at the API test facility in , , using a standard that simulates twice the radioactivity of an average mid-continent U.S. formation. Specifically, 1 unit equals 1/200th of the difference between the count rate in this standard and a low-radioactivity zone. Logs are commonly displayed on a from 0 to 150 units. Borehole conditions necessitate quantitative corrections to mitigate distortions in readings. Mud invasion, particularly from potassium-laden drilling fluids, adds extraneous near the wellbore, while and enlarged diameters increase signal or dilution effects. These factors can introduce variability of 10-20% in measured counts, depending on size and fluid composition, requiring empirical or model-based adjustments for accurate .

Spectral Gamma Ray Logging

Spectral gamma ray logging represents an advanced variant of measurement that discriminates s by their energy levels to identify and quantify concentrations of specific radioelements, primarily (K), (Th), and (U), within subsurface formations. This technique utilizes multichannel analyzers coupled with detectors, such as (NaI(Tl)), to sort incoming pulses into discrete energy bins or windows, enabling the isolation of characteristic emissions from natural series. For instance, energy windows are typically defined as 1.37–1.57 MeV for , 1.66–1.87 MeV for , and 2.46–2.78 MeV for , allowing real-time computation of elemental counts during logging operations. The method achieves isotope resolution by focusing on prominent gamma ray peaks in the full spectrum: 1.46 MeV from the decay of ^{40}K, 1.76 MeV from ^{214}Bi in the ^{238}U series, and 2.62 MeV from ^{208}Tl in the ^{232}Th series. These peaks facilitate the derivation of elemental ratios, such as Th/K, which serve as indicators for distinguishing clay mineral types—lower Th/K values often correlate with kaolinite-rich clays, while higher ratios suggest illite or mixed-layer clays. This elemental differentiation provides enhanced lithological and mineralogical insights compared to total-count methods, which aggregate all emissions without energy discrimination. Modern spectral gamma ray tools incorporate enhancements like multiple NaI detectors arranged in arrays for improved vertical and reduced borehole effects, alongside advanced pulse-height electronics to process spectra with up to 256 channels. Energy in these systems typically ranges from 5–8% at 1.33 MeV, enabling clearer separation of overlapping peaks despite the inherent limitations of NaI scintillators. As of 2025, recent advancements include the integration of for spectral deconvolution, which addresses challenges like Compton scattering-induced overlaps and energy drift by employing models to reconstruct underlying spectra from . For example, back propagation neural networks applied to uranium spectral logging have demonstrated accuracies exceeding 93% for medium- to high-grade ores, even at elevated logging speeds of 6 m/min, thereby improving quantitative reliability in complex environments.

Applications

In Petroleum Exploration

In petroleum exploration, gamma ray logging serves as a fundamental tool for formation evaluation and reservoir characterization in oil and gas wells, enabling the identification of lithological variations and the assessment of content within hydrocarbon-bearing formations. This technique is particularly valuable in shaly reservoirs, where it helps quantify the volume of (V_shale) to correct and permeability estimates, thereby improving calculations. The (I_GR), defined as I_{GR} = \frac{GR_{log} - GR_{min}}{GR_{max} - GR_{min}}, provides a normalized measure of content, where GR_log is the recorded value, GR_min represents the clean baseline (typically 20-50 units), and GR_max indicates the pure response (often 100-150 units). This is widely applied to estimate V_shale in shaly sands, with linear transformations such as V_shale ≈ I_GR used for initial approximations, though nonlinear models may be employed for more accurate field-specific calibrations. Gamma ray logs also facilitate well-to-well correlation and stratigraphic mapping by revealing deflection patterns that distinguish lithologies: high gamma ray values (above 80-100 units) typically indicate shales rich in radioactive minerals like and , while low values (below 50 units) signify clean sands or carbonates. These patterns allow geologists to match formations across wells, aiding in the identification of reservoir boundaries and structural features for regional stratigraphic frameworks in sedimentary basins. Integration of gamma ray data with other logs enhances net pay determination and drilling decisions. For instance, combining with resistivity and logs (e.g., neutron-density) helps delineate hydrocarbon-bearing intervals by applying shale cutoffs to exclude high V_shale zones, thus isolating effective in sands where resistivity exceeds 5-10 ohm-m and is above 10-15%. In real-time (LWD) applications, azimuthal tools provide directional data for geosteering, enabling operators to maintain well trajectories within optimal reservoir zones during horizontal . For example, in the Permian Basin's Wolfcamp formation, logs are used for lateral correlations and well trajectory steering in thin-bedded reservoirs. In unconventional plays like the Ford, LWD tools are used for precise geosteering, as demonstrated in wells where real-time data improved landing accuracy in organic-rich intervals and boosted production.

In Mineral and Groundwater Exploration

In mineral exploration, gamma ray logging plays a crucial role in detecting radioactive anomalies associated with bodies, particularly those containing and . For , the technique identifies pitchblende and other uranium-bearing minerals through elevated gamma emissions from decay series, enabling accurate delineation of ore grades and thicknesses in boreholes without extensive sampling. Spectral gamma ray logging enhances this by distinguishing from and contributions. In exploration, high emissions signal sylvinite or deposits, with gamma ray responses typically ranging from 120 to 270 API units; grade-thickness products are calculated as GT = KA, where A integrates the gamma ray response over depth, allowing non-invasive grade estimation. For groundwater exploration, gamma ray logging maps clay content to assess aquifer permeability, as shales and clays exhibit higher natural radioactivity due to thorium and potassium enrichment. An optimized clay index, derived from processed gamma ray values normalized to a beta distribution, estimates clay percentages from 15% to 54% in water-bearing layers, aiding hydraulic conductivity predictions. Thorium-to-potassium ratios from spectral logging further delineate aquifer boundaries by highlighting lithologic transitions in sedimentary sequences. Environmental applications include monitoring in boreholes, where spectral gamma logging quantifies or anomalies at waste sites, as demonstrated in Canadian studies identifying in and mitigating interference. Integration with other geophysical surveys supports site remediation by mapping contaminant plumes. In global examples, gamma ray logging has been integral to Australia's post-2010 uranium boom, with downhole surveys in projects like the deposit confirming distributions. In Europe, recent studies up to 2023 in used gamma ray logs to detect low-permeability clay lenses in contaminated aquifers, improving 3D models for VI remediation.

Interpretation and Analysis

Lithology Identification

Gamma ray logging enables qualitative lithology identification primarily through the recognition of distinct radioactivity patterns, as natural gamma radiation varies significantly with rock composition. Shales and clays, rich in radioactive isotopes such as potassium-40, thorium-232, and uranium-238 concentrated in clay minerals, typically produce high gamma ray deflections exceeding 100 API units. In contrast, clean sandstones and limestones, which contain fewer radioactive elements, exhibit low readings generally below 30 API units. These baseline patterns allow geologists to differentiate argillaceous from non-argillaceous formations at a glance. Anomalous high gamma ray readings can signal the presence of specific minerals or deposits that deviate from standard lithologic trends, such as in sands or layers, which elevate content and thus . For instance, often manifests as sharp spikes due to its high concentration, while beds may show elevated or levels. These anomalies aid in pinpointing depositional environments or diagenetic alterations but require contextual verification to avoid misinterpretation. Qualitative analysis is enhanced by integrating gamma ray patterns with other well logs for confirmation, such as neutron-density crossovers, where the separation between curves helps distinguish lithologies like (high crossover) from or (low or no crossover). Additionally, the shape of gamma ray deflections provides clues about bed thickness: abrupt, square-shouldered deflections indicate thicker beds with uniform , whereas gradual or rounded transitions suggest thinner layers or gradational contacts. In complex formations, however, limitations arise, as potassium-feldspar-rich arkosic sands can produce misleadingly high readings that mimic shaliness despite their siliceous nature. Visual log motifs further illustrate depositional sequences through gamma ray trends. For example, bell-shaped motifs, where readings increase upward from low to high values, are indicative of fining-upward sequences, such as those in point bars or tidal channels, reflecting a transition from coarser sands at the base to finer shales at the top. These patterns, observable on conventional total logs, facilitate rapid stratigraphic and environmental .

Quantitative Evaluation Techniques

Quantitative evaluation techniques in gamma ray logging involve mathematical models and computational methods to derive precise petrophysical properties from raw log data, such as volume and geochemical indicators. These approaches transform the gamma ray index (IGR), defined as I_{GR} = \frac{GR - GR_{clean}}{GR_{shale} - GR_{clean}}, where GR is the measured value, GR_clean is the response in clean , and GR_shale is the response in pure , into quantifiable parameters. Shale volume (V_sh) models are fundamental for estimating clay content, with the Larionov equations providing non-linear transformations to correct for the non-linear response of gamma rays in shaly formations. For Tertiary rocks, the equation is: V_{sh} = 0.083 \left( 2^{3.7 I_{GR}} - 1 \right) This formulation, originally proposed in 1969, accounts for the exponential increase in gamma ray response with shale content in younger sediments. For older formations, an adapted version uses: V_{sh} = 0.33 \left( 2^{2 I_{GR}} - 1 \right) This adjustment reflects differences in mineralogy and compaction in pre-Tertiary rocks, reducing overestimation in linear models. Spectral gamma ray logging enables quantitative geochemical analysis through ratios of radioelement concentrations. The thorium-to-uranium (Th/U) ratio serves as a proxy for redox conditions during deposition, with values below 2 indicating reducing environments where uranium is immobilized, such as in marine black shales, while ratios above 7 suggest oxidizing conditions typical of terrestrial settings with uranium leaching. Potassium content, measured in weight percent, aids mineralogical identification; elevated levels (e.g., >1%) often signify illite-rich clays, distinguishing them from low-potassium minerals like kaolinite or smectite via thorium-to-potassium (Th/K) cross-plots. Monte Carlo simulations address uncertainties in gamma ray data, particularly in high-noise environments like slim-hole drilling or variable borehole conditions, by propagating input errors through thousands of iterations to generate probabilistic distributions of outputs such as V_sh. These methods model statistical variations in counting rates and tool responses, providing confidence intervals for interpretations. As of 2025, integrations with machine learning enhance predictive modeling; hybrid physics-ML frameworks combine Larionov-type equations with algorithms like artificial neural networks (ANN) and random forests, achieving root mean square errors as low as 0.062 for V_sh predictions when trained on gamma ray and auxiliary logs, outperforming standalone classical or ML approaches in complex carbonate reservoirs. Error analysis in quantitative evaluations focuses on uncertainty propagation from calibration, where gamma ray tools are standardized to American Petroleum Institute (API) units using test pits; typical statistical counting errors contribute uncertainties on the order of a few percent in API readings (e.g., ±2-5 API in standard conditions), which amplify in derived parameters like V_sh through non-linear functions. Calibration mismatches or environmental factors, such as borehole rugosity, necessitate error budgeting via sensitivity tests to ensure reliable petrophysical outputs.

Advantages and Limitations

Key Benefits

Gamma ray logging offers significant versatility in environments, functioning effectively in both open and cased holes due to the penetrating nature of gamma rays through steel casing. This method is also unaffected by formation fluids, size, or pressure variations, as it passively measures naturally occurring without interference from these factors. In terms of cost-effectiveness, gamma ray logging tools are relatively inexpensive to deploy, enabling quick integration into standard well log suites where it serves as a fundamental tool. Its rapid deployment and low maintenance requirements make it an essential component in nearly every logging program, minimizing overall expenses compared to more complex methods. The real-time capabilities of logging-while-drilling (LWD) gamma ray tools allow for immediate during , facilitating on-the-fly adjustments to well trajectory and reducing non-productive time by 10-20% through proactive hazard avoidance and optimized placement. Environmentally, logging is non-invasive, requiring no chemicals or active sources, which ensures minimal ecological impact and aligns with IAEA guides for low risks in using passive techniques.

Technical Challenges

One major technical challenge in gamma ray logging is the limited vertical , typically ranging from 2 to 5 feet (0.6 to 1.5 meters), which arises from the tool's detector spacing, logging speed, and sampling rate. This resolution often fails to detect thin beds or subtle lithological transitions in heterogeneous formations, leading to smoothed or averaged readings that obscure fine-scale geological features. Additionally, statistical noise is prominent in low-count environments, such as clean sandstones with minimal natural radioactivity, due to the stochastic nature of gamma ray emissions and low detection rates. Environmental interferences further complicate accurate measurements, with borehole rugosity—irregular wall surfaces caused by drilling—introducing air gaps or uneven tool contact that can distort signal reception. Such , along with variations in size, mud density, and fluid invasion, can cause signal attenuations or enhancements, particularly in uncased holes, exacerbating inaccuracies in heterogeneous formations where thin beds amplify these effects. These factors necessitate environmental corrections during to mitigate distortions. Interpretation of gamma ray logs is prone to pitfalls, especially ambiguities from non-shale formations exhibiting elevated radioactivity, such as sands containing micas, K-feldspars, or , which can produce readings as high as those in adjacent shales (up to 200 units). These "hot" sands, often from immature sediments near basement terranes, may be misidentified as shales, leading to erroneous assessments without cross-validation using core samples or complementary logs. Recent advancements address these challenges through dual-detector tools that enhance statistical reliability by increasing count rates and enabling better noise reduction via differential measurements. Additionally, AI-based denoising algorithms, including thresholding and fuzzy Kalman smoothers, have emerged since 2020 to statistical noise and deconvolve logs, improving in low-count scenarios. As of 2025, enhanced methods allow gamma ray logging through strings, further improving applications in cased boreholes. These methods, validated in field applications, reduce interpretation errors by up to 20-30% in noisy datasets.

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