A Method for Calculating More Accurate Stratigraphic Positioning of Horizontal Wells Using Continuous Inclination and Azimuthal Gamma Ray Images Even While Sliding
Abstract: Geosteering long lateral wells in narrow target windows demands accurate stratigraphic positioning, true vertical depth (TVD) positioning, and apparent dip determinations. Using positive displacement motors with alternating slide and rotate drilling modes to control the well trajectory, along with standard 90-ft surveys and single-detector azimuthal gamma ray (GR) tools, have proven to be inadequate. To overcome these issues, a new method has been developed that combines continuous measurements and uses a four… Show more
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Cited by 4 publications
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Azimuthal gamma ray (GR) logging-while-drilling (LWD) tools have demonstrated great value for geosteering applications in directional drilling. Their ability to indicate the relative stratigraphic position of the drilling assembly can determine whether the well should be steered up or steered down to stay in the target zone. However, this determination remains rather qualitative and largely depends on the user experience, especially when the quality and amount of real-time data is limited by intrinsic statistical noise, telemetry bandwidth, rate of penetration (ROP), and other drilling conditions. In addition, the commonly used geosteering modeling for azimuthal GR is geometry based only, without considering any measurement physics. Thus, a new forward-modeling and inversion method has been developed to provide an optimized pre-job planning and potentially quantitative real-time decision-making for more accurate geosteering with azimuthal GR. The geosteering question can be simplified mathematically to a prediction of separation between azimuthal GR curves when approaching or passing a bed boundary in a two-bed formation model. Separation will give an indication of a steering direction change, even in the simplest case of only up- and down-facing GR curves. In this study, a method was developed to solve this question in seconds with only two factors: measurement precision and front-to-back ratio. The theoretical up- and down-facing readings of an azimuthal GR tool can be forward-modeled accurately from this ratio for any bed boundary changes. Combined with measurement precision, the counting statistics effects can be added to the model to mimic the real-world log curves, and this for any pre-selected stratigraphic marker. The forward model results agree well with industrial standards of full Monte Carlo nuclear simulation and its deterministic nature allow it to run very fast. Thus, various scenarios can be evaluated quickly during either the pre-well phase or the operation. Detection limits achieved by any azimuthal GR tool in any given scenario can be statistically predicted for various confidence levels (e.g., 95% possibility of up/down curve separation). Thus, based on the detection limits, confidence level, and their variation with ROP, .etc. the drilling and geosteering plan can be optimized to reach the best ROP confidently without compromising the steering capability. Also in real time, when a potential separation of up- and down-facing azimuthal GR curves appear on the log, inversion of this model can be carried out to derive the possibility that this separation truly reflects formation changes to offer some quantitative insight to make steering decisions. Inversion of the modeling also has the potential to help recover the true API values of the formation beds and enhance the detection of the bed boundary positions. The novelty of this approach stems from the statistical nature of nuclear counting statistics and the derivation of front-to-back ratio. Front-to-back ratio, when properly defined, is a factor that fully represents the measurement physics of the tool. In addition to the aforementioned applications, an overall coverage chart can be recalculated as a quick look-up reference to measure the effectiveness of azimuthal GR. The chart reflects the detection limits that an azimuthal GR tool can resolve for geosteering in a 0–200-API sampling space at a certain confidence level. Overall, the paper includes a detailed description of the model and its inversion, applications, and example log demonstrations from early trials.
Azimuthal gamma ray (GR) logging-while-drilling (LWD) tools have demonstrated great value for geosteering applications in directional drilling. Their ability to indicate the relative stratigraphic position of the drilling assembly can determine whether the well should be steered up or steered down to stay in the target zone. However, this determination remains rather qualitative and largely depends on the user experience, especially when the quality and amount of real-time data is limited by intrinsic statistical noise, telemetry bandwidth, rate of penetration (ROP), and other drilling conditions. In addition, the commonly used geosteering modeling for azimuthal GR is geometry based only, without considering any measurement physics. Thus, a new forward-modeling and inversion method has been developed to provide an optimized pre-job planning and potentially quantitative real-time decision-making for more accurate geosteering with azimuthal GR. The geosteering question can be simplified mathematically to a prediction of separation between azimuthal GR curves when approaching or passing a bed boundary in a two-bed formation model. Separation will give an indication of a steering direction change, even in the simplest case of only up- and down-facing GR curves. In this study, a method was developed to solve this question in seconds with only two factors: measurement precision and front-to-back ratio. The theoretical up- and down-facing readings of an azimuthal GR tool can be forward-modeled accurately from this ratio for any bed boundary changes. Combined with measurement precision, the counting statistics effects can be added to the model to mimic the real-world log curves, and this for any pre-selected stratigraphic marker. The forward model results agree well with industrial standards of full Monte Carlo nuclear simulation and its deterministic nature allow it to run very fast. Thus, various scenarios can be evaluated quickly during either the pre-well phase or the operation. Detection limits achieved by any azimuthal GR tool in any given scenario can be statistically predicted for various confidence levels (e.g., 95% possibility of up/down curve separation). Thus, based on the detection limits, confidence level, and their variation with ROP, .etc. the drilling and geosteering plan can be optimized to reach the best ROP confidently without compromising the steering capability. Also in real time, when a potential separation of up- and down-facing azimuthal GR curves appear on the log, inversion of this model can be carried out to derive the possibility that this separation truly reflects formation changes to offer some quantitative insight to make steering decisions. Inversion of the modeling also has the potential to help recover the true API values of the formation beds and enhance the detection of the bed boundary positions. The novelty of this approach stems from the statistical nature of nuclear counting statistics and the derivation of front-to-back ratio. Front-to-back ratio, when properly defined, is a factor that fully represents the measurement physics of the tool. In addition to the aforementioned applications, an overall coverage chart can be recalculated as a quick look-up reference to measure the effectiveness of azimuthal GR. The chart reflects the detection limits that an azimuthal GR tool can resolve for geosteering in a 0–200-API sampling space at a certain confidence level. Overall, the paper includes a detailed description of the model and its inversion, applications, and example log demonstrations from early trials.
Real-Time Wellbore Placement Improvement with High-Fidelity Trajectory Estimation and Dual-Sensor MWD Packages
High-fidelity trajectory estimation combined with dual-probe Measurement-While-Drilling (MWD) directional instrumentation provides a solution to minimum curvature’s known inefficiencies in modeling the true wellbore position and definition (Stockhausen & Lesso, 2003). While it may not be cost efficient to increase survey frequency from the industry standard of 30ft-200ft, it is possible using the techniques defined in this research to maintain current survey intervals and increase wellbore placement accuracy while reducing positional uncertainty by up to 45% over the most advanced commercially available magnetic survey correction algorithms. Taking advantage of modern MWD tool platforms enables the installation of an additional (30-inch) survey measurement probe in the existing tool string with a fixed and known offset to the primary survey probe. Directional surveys from both survey probes are telemetered to surface at traditional course length survey intervals in real-time. The two surveys along with the known steering and non-steering intervals are processed through a high-fidelity trajectory estimation algorithm to quantify the wellbore behavior between survey stations. The result is a highly accurate and dense survey listing with modeled trajectory waypoints between traditional surveys to reduce the course length between directional measurement datapoints and better capture the true well path. Through extensive lab modeling, it was determined that the use of the dual-probe MWD package in combination with the high-fidelity trajectory estimation algorithm could result in a reduction in the Ellipse of Uncertainty (EOU) by 20% in the horizontal (semi-major) plane and 45% in the vertical (semi-minor) plane when compared to Multi-Station Analysis (MSA) and BHA Sag survey correction techniques. In addition to proof-of-concept modeling, the system has been deployed and used in real-time application on three separate pads, totaling nine wells. The results were able to validate and exceed baseline goals by exhibiting, on average, a reduction of the EOU by 21% in the horizontal plane and 58% in the vertical plane. Further, True Vertical Depth (TVD) error at well Total Depth (TD) in excess of 10ft was observed on three out of nine wells (33%) in this limited real-time application study. This difference was relative to separate, concurrent processing of the surveys via Multi-Station Analysis (MSA) and BHA sag corrections. This level of increased TVD accuracy is significant in many applications, depending on zone thickness and difficulty of geological interpretation. Increased accuracy and reduced uncertainty result from a better understanding of the true well path between traditional course length surveys. The trajectory estimation algorithm quantifies the rotational build/drop and walk rates in real-time and is reinforced by the dual-probe directional survey measurements. These tendencies can be used to better project forward to the bit as the well is drilled. Improved projection to the bit allows for enhanced recognition of deviation from the well plan and better-informed steering decisions.
A Comparison of High-Resolution Trajectory Methods and Their Impact on Drilling Data Analysis
Wellbore trajectories are a fundamental piece of data used for decisions throughout the oilfield. Trajectories are typically mapped through measurement-while-drilling (MWD) survey stations collected at 95ft intervals. Previous work suggests that this sparse sampling interval masks short segments of high curvature, negatively impacting workflows that consume this data (Stockhausen & Lesso, 2003; Baumgartner, et. al., 2019). This can come in the form of poorly estimating the true vertical depth of a well, poorly mapping geologic structure, and poorly quantifying the tortuosity of the wellpath. Several methods have previously been proposed to improve trajectory mapping by incorporating additional data collected between stationary surveys (Stockhausen & Lesso, 2003; Gutiérrez Carrilero, et al., 2018). Two sources of such data are continuous survey measurements and slide/rotate behaviors captured in slide sheets. Two methods of improving the wellbore trajectory mapping were compared in several extended reach lateral wellbores. The impact of the new trajectories on landing point selection, dip estimation, and wellbore tortuosity analysis was determined. One method took continuous inclination data and mapped directional changes between stationary surveys. The second used bit projections generated through automated-slide-sheet-analysis from real-time tool face data, estimating the location and direction of curvature produced by slide/rotate operations. These curvature estimations were used to predict wellbore shape between surveys. As a final check, in the curve sections of the wellbores, stationary surveys were collected at more frequent intervals (e.g., 31ft) to provide validation on the high-resolution trajectories and to understand the cost-benefit of simply surveying more frequently. Both methods of high-resolution trajectories imply that errors present in a 95ft course length survey are enough to impact decisions made when drilling an extended reach lateral. Landing point estimations were shifted in several cases by over 10ft, the approximate thickness of the target formation. Similar discrepancies in true vertical depth were observed along the length of the laterals. Both methods showed strong agreement through the curve sections of the wellbore, however this agreement weakened during the lateral where short slides and geological effects on rotary tendency reduced the accuracy of the automated-slide-sheet method. A discussion of the discrepancies between the two methods in laterals is included. Dogleg severity analysis confirmed that short sections of high curvature exist that are masked by traditional 95ft survey course lengths. Surveying at 31ft intervals improves the mapping of this tortuosity but still does not capture the full effects seen on continuous survey data. Previous work has suggested that typical wellbore trajectory mapping may be unsuitable for accurate analysis of things like geological structure and wellbore tortuosity analysis. Two methods are evaluated here that support those claims, suggesting that in the future high-resolution trajectories may be a necessity for accurate decision-making.
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