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Collaborating Authors
Inversion Of Sector-Based Lwd Density Measurements Acquired In Laminated Sequences Penetrated By High angle And Horizontal Wells
Mendoza, Alberto (Retired, formerly Baker Hughes, Inc.) | Torres-Verdin, Carlos (The University of Texas at Austin) | Preeg, Bill (Consultant) | Rasmus, John (Schlumberger) | Radtke, R.J. (Schlumberger) | Stockhausen, Ed (Chevron)
We show that inversion processing improves the petrophysical interpretation of logging-while-drilling (LWD) density measurements acquired in high-angle and horizontal (HA/HZ) wells. Our interpretation method consists of first detecting bed boundaries from short-spacing (SS) detector and bottom-quadrant compensated densities by calculating their variance within a sliding window. Subsequently, a correlation algorithm calculates dip and azimuth from the density image. Depth shifts that vary azimuthally and depend on relative dip angle, together with the effective penetration length (EPL) of each sensor, refine previously selected bed boundaries. Subsequently, inversion combines all the sector-based density measurements acquired at all measurement points along the well trajectory to estimate layer densities. We implement the inversion with a recently developed linear approximation that accurately and efficiently simulates borehole density measurements. To verify the reliability and applicability of the inversion method, we first use forward simulations to generate synthetic density images from a model constructed from field data. Results indicate that inversion improves the interpretation of azimuthal density data as it consistently reduces shoulder-bed effects. We appraise inversion results obtained from field measurements by quantifying the corresponding integrated porosity-feet yielded by inversion methods in comparison to standard techniques that use simple cutoffs on field-processed compensated density. Integrated porosity-feet of inverted synthetic density measurements increase by 4.4% with respect to noninverted field measurements. By comparison, integrated porosity-feet from inversion results that include only bottom sectors improve by 27.8% with respect to that calculated with field-compensated, bottom-quadrant density measurements. Experience shows that an additional benefit of inversion methods is their ability to detect and quantify the inaccuracies attributed to increasing tool standoff in the upper sectors of the measurement. INTRODUCTION Conventional processing of LWD density measurements in HA/HZ wells may not yield results with sufficient spatial resolution to estimate actual layer density. This situation commonly arises when using standard compensation (spine-and-rib method) of single-detector density measurements acquired in thin laminations. Unlike in vertical wells, it has been shown that enhanced-resolution processing does not improve the resolution of compensated density in HA/HZ wells (Radtke et al., 2006; Mendoza et al., 2006). Accurate estimation of true stratigraphic thickness (TST) and density-derived porosity is essential for reliable calculations of net pay. Because existing standard and enhanced-resolution compensation methods were designed for vertical wells, other authors have expressed a need for compensation techniques suitable for HA/HZ wells. Recent publications on Monte-Carlo simulation of azimuthal density measurements propose alternative post-processing techniques of raw density images acquired across thin laminations in HA/HZ wells (Uzoh et al., 2009; Yin et al, 2008). Our approach is to utilize inversion methods to calculate more accurate layer properties for subsequent use in petrophysical interpretations. The proposed inversion technique eliminates shoulder-bed effects due to the high apparent dip observed in HA/HZ wells and improves the estimation of bed petrophysical properties, specifically porosity and fluid saturation, based on simulation of nuclear measurements. Historically, the lack of fast and reliable numerical simulation methods constrained the applicability of inversion methods for petrophysical interpretation of nuclear measurements. Patchett and Wiley (1994) used an iterative inverse modeling procedure to determine porosity, water saturation, and lithology with a forward modeling algorithm that simulated nuclear logs based on elemental composition of the rocks and fluids.
- Europe (1.00)
- North America > United States > Texas (0.94)
- Geology > Geological Subdiscipline > Stratigraphy (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.46)
Applying current between the electrodes Wireline-logging measurements provide establishes a potential field, This study used the opposite protocol. Such which is a function of the unknown Although the adjacent method measurements rely on sources that conductivity distribution. The electric generates more unique data points, the direct signals outward into the formation, field on the boundary is sampled opposite protocol tends to produce then detect the formation with other flush-mounted electrodes. Scattering induced by the The current drive pair of electrodes ratio. Thus, the number of reservoir rock is interpreted in terms then can be switched and more measurements high-quality unique measurements is of formation properties.
Continuous Rock Strength Measurements On Core And Neural Network Modeling Result In Significant Improvements In Log-Based Rock Strength Predictions Used To Optimize Completion Design and Improve Prediction of Sanding Potential and Wellbore Stability
Suarez-Rivera, Roberto (TerraTek) | Ostroff, Gary (BHP Billiton Petroleum (Americas) Inc.) | Tan, KaiSoon (BHP Billiton Petroleum (Americas) Inc.) | Begnaud, Bill (BHP Billiton Petroleum (Americas) Inc.) | Martin, Wesley (TerraTek) | Bermudez, Tony (TerraTek)
Abstract The scaling-up of laboratory rock mechanical measurements from sample-scale to reservoir-scale is fundamental to evaluation of wellbore stability, sanding potential, reservoir compaction or casing failure. Understanding rock heterogeneity is fundamental for adequate scaling-up laboratory measurements to core- and reservoir-scales and thus, to predictions of mechanical failure. Historically, scaling-up from core scale to reservoir scale has been dependent on calibration of log-based models to a sparsely sampled data set of rock mechanical property measurements made on core plugs. Such a sparsely sampled data set of core plug measurements alone may inadequately characterize the range heterogeneities in the reservoir, resulting in less than optimum log-based predictive models. With the introduction of continuous, high resolution, rock strength (UCS) measurements on core via scratch testing, an excellent calibration reference for producing robust log-based predictions of rock strength now exist. In this study, high-resolution measurements of strength heterogeneity were obtained as a function of core length and were correlated with fundamental textural and compositional parameters from petrographic analysis. Using adaptive learning neural networks, fundamental relationships between log measurements and rock strength were obtained. This methodology was adequate for characterizing the intrinsic rock heterogeneity at appropriate scales for mechanical analysis of completion design and sanding (0.25 ft). The methodology is also potentially applicable to the scaling-up of other fundamental mechanical properties such as in-situ strength, compressibility and thick-walled cylinder strength. Results show that intrinsic textural heterogeneity and strength heterogeneity are strongly related in sedimentary rocks. Recognizing the importance of rock heterogeneity and being able to scale-up this property to core and reservoir scales via log measurements results in significant improvements in the predictive capacity for sanding potential and wellbore stability. For example, thin layers of considerably weaker-strength than the surrounding rock, undetectable from conventional log-based rock strength predictions, were detected and included in the mechanical model. In addition to possessing high sanding potential, these weaker sections are also regions of fluid loss during drilling. Results can be used for selection of competent rock across the field (based on LWD measurements) for multilateral junction placement, and for selection of optimum completion strategies. Introduction Rock mechanics evaluations of wellbore stability, sanding potential, reservoir compaction or casing failure require the scaling-up of fundamental laboratory measurements of rock mechanical properties from sample-scale to reservoir-scale. This scaling-up of mechanical properties is often conducted via correlation with log measurements and thus, log-based correlations of rock properties (primarily strength and elastic moduli) are of fundamental importance for drilling, completion, and long-term production calculations. Historically, scaling-up from core scale to reservoir scale has been performed using sparsely sampled data sets of rock mechanical property measurements made on core plugs. As such sparsely sampled data sets of core plug measurements are not likely to adequately characterize the range heterogeneities in the reservoir, less than optimum log-based predictive models have typically been the result.
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.48)
Invasion Corrected Fluid Saturations, from Standalone Consonant Nuclear Measurements, Using Canonical-Correlation Analysis (CCA) of Logging-While-Drilling (LWD) Time-Lapse Data
Al-Daghar, Khadeeja A. (SPE) | Atfeh, Mudar M. (SPE) | Aal, Atef F. (Abu Dhabi Company for Onshore Operations (ADCO)) | Jain, Vikas (SPE) | Murray, Doug R. (SPE) | Minh, Chanh Cao (SPE) | Gzara, Kais (Schlumberger)
Abstract Fluids saturations in new wells are usually derived from resistivity measurements, using locally selected or calibrated resistivity equations. Some drawbacks to resistivity measurements are multiple environmental corrections in high-angle wells, thin beds, washed-out boreholes, and complex invasion profiles. Moreover, the accuracy of Archie's equation may suffer from variable cementation and saturation exponents and unknown water salinity. A recently introduced comprehensive suite of consonant logging-while-drilling (LWD) nuclear measurements with linear mixing laws, is used to solve for minerals and fluid volumes independent of resistivity measurements. This requires the petrophysical properties of all the fluids present to be known. Another requirement for accurate formation evaluation is the mud filtrate invasion correction. While this poses no problem for multiple depths of investigation (MDOI) resistivity measurements that also read deep into the formation, there is no set rule to determine the geometrical factor of nuclear measurements to account for invasion. This paper describes an LWD time-lapse data acquisition scheme to circumvent invasion effects on nuclear measurments and to eliminate the need to specify some of the unknown petrophysical properties of the fluids present. Canonical-correlation analysis (CCA) is used to identify canonical variates that remain unchanged between a primary drill pass and a secondary wipe pass. Because these variates remain unchanged between passes, they are independent of the formation invasion status, and can represent the properties of either the virgin or the flushed zone, but not a combination of the two, as is typically the case of measurements whose volume of investigation samples both zones. These invasion-independent variates are then used in the petrophysical evaluation, instead of the standard logs which may otherwise vary with time. We used CCA in 2 carbonate examples to show how to 1) correct bulk density measurement in corkscrew borehole, 2) correct MDOI capture sigma measurements for invasion effect, and 3) perform volumetric formation evaluation without knowledge of the water and hydrocarbon endpoints and invasion parameters. The CCA approach is a significant new development in well log interpretation that removes uncertainties associated with unknown mineral or fluids petrophysical properties and invasion status.
- North America > United States (0.94)
- Asia (0.68)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Core analysis (1.00)
In-Well Stress Shadow and Near-Wellbore Fracture Geometry Diagnosis Using High-Resolution Distributed Strain Sensing via Rayleigh Frequency Shift
Srinivasan, Aishwarya (Texas A&M University) | Jurick, Dana (Neubrex Energy Services) | Haustveit, Kyle (Devon Energy) | Jin, Ge (Colorado School of Mines) | Guzik, Artur (Neubrex Co., Ltd.) | Wu, Kan (Texas A&M University)
Abstract Rayleigh Frequency Shift based Distributed Strain Sensing (RFS-based DSS) is a novel fiber optic diagnostic technique capable of measuring strain changes with a spatial resolution as low as 20 cm and measuring sensitivity as small as 1 με. RFS-based DSS measurements rely on the frequency shifts of the Rayleigh backscattered spectrum, which is sensitive to temperature and mechanical strain changes. This work uses in-well RFS-based DSS and DTS measurements acquired during a single-stage stimulation. The goal is to quantify the mechanical strain changes by removing the temperature effects from the RFS-based DSS measurements using the DTS measurements and gain insights into the in-well stress shadow and near-wellbore fracture connectivity. A new stage was stimulated in an already stimulated fiber well above the heel-most perforation. A cast iron bridge plug (CIBP) was placed between the heel-most perforation and the new stage to prevent fluid leakage. The RFS-based DSS measurements exhibit high spatial variations at the new stage depth than the DTS measurements due to the combined effects of temperature and mechanical strain effects. The temperature change from DTS measurements is converted to corresponding RFS-based DSS measurements using a scaling coefficient. The scaled temperature change is subtracted from the RFS-based DSS measurements to obtain the mechanical strain change. A geomechanical model is used to understand the strain and strain-rate changes during a single fracture propagation from the fiber well. The temperature change obtained from the DTS measurements shows an adiabatic heating effect of wellbore fluid at the depths below the new stage and the CIBP. The RFS-based DSS measurements show a compression effect at the depths between the new stage and CIBP, contradictory to temperature change. The mechanical strain change obtained after removing the temperature effect shows a compression effect up to ∼300 ft below the injection depth at the end of the pumping, whereas the temperature change measurements show the cooling effect due to injection exists for ∼60 ft below the injection depth. This difference demonstrates the intensity of the in-well stress shadow effects. This work is the first analysis to utilize high-resolution in-well RFS-based DSS measurements to understand the stress shadow effects and near-wellbore geometry. This work provides key information to understand the relation between strain and treatment pressure responses and their association with near wellbore fracture conductivity.
- North America > United States > Texas (0.30)
- North America > United States > New Mexico (0.28)
- North America > United States > Texas > Permian Basin > Delaware Basin (0.99)
- North America > United States > New Mexico > Permian Basin > Delaware Basin (0.99)
- Europe > Netherlands > Groningen > Southern North Sea - Anglo Dutch Basin > Groningen License > Groningen Field > Upper Rotliegend Formation (0.99)
- Europe > Netherlands > Groningen > Southern North Sea - Anglo Dutch Basin > Groningen License > Groningen Field > Limburg Formation (0.99)
- Well Completion > Hydraulic Fracturing (1.00)
- Well Completion > Completion Monitoring Systems/Intelligent Wells > Downhole sensors & control equipment (1.00)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (1.00)