SPWLA HAHZ SIG 2025 Workshop 1
About
Welcome to SPWLA HAHZ SIG's Workshop for 2025.THIS EVENT IS A VIRTUAL EVENT, ATTENDANCE WILL BE VIA TEAMS MEETING
WORKSHOP 1 will be hosted online to correspond with Europe and Middle East Timezone.
Wednesday 5th November, 2am Houston, 9am Paris, 12pm Dubai, 4pm Singapore
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WORKSHOP 1 PRESENTERS:
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Harald Bolt, DwpD Ltd., Depth Solutions - Quantification, and Value Impact, of Vertical Depth Uncertainty
Juan Ariza, SLB - Workflow For Modeling Expected Responses of Petrophysical Measurements In High-angle Wells Using Geological Understanding To Quantify Impact On Reservoir Evaluation And Structural Definition
Mohamed Fouda, Haliburton - Towards Well Placement Automation; Revolutionizing Geo-steering with Automated Dip Picking from Image and Boundary Mapping from Azimuthal Resistivity Multi-Layer Inversions
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ABSTRACTS:
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Quantification, and Value Impact, of Vertical Depth Uncertainty
Harald Bolt, DwpD Ltd., Depth Solutions
Uncertainty in subsurface models stems from both the accuracy of acquired data and the calculation methods employed. Subsurface well positioning and positional uncertainty are key to describing not only the geometry of the wells but the localization of geologies, reservoirs, fluid interfaces, other geological events (faults, seals, gradients, etc.), through to hydrocarbon initially in place (HCIIP) estimation. These uncertainties directly affect the value of hydrocarbon initially in place (HCIIP) estimates, which underpin critical economic decisions about the viability of subsurface prospects. Key input parameters—including gross reservoir volume, sand count, porosity, fluid saturation, and conversion factors—are derived from a combination of seismic interpretation, wellbore measurements, petrophysical evaluation, and fluid characterization.
Traditionally, Vertical depth, and hence volumetric, uncertainty has been characterized by simplified rule-of-thumb and industry standard (ISCWSA) approaches. Particularly in high-angle and horizontal (HAHZ) wells (e.g. Fig. 1), the possible positional variances can be significant. Without management of expectations, this can lead to unbounded uncertainty.
This presentation introduces 3D Way-point, a rigorous framework for quantifying subsurface 3D positional uncertainty. 3D Way-point is an advanced, yet conceptually easy to understand, tool that allows position and positional uncertainty to be calculated and reported in easy-tounderstand terms. 3D Way-point improves the fidelity of reported results and, most importantly, explicitly links technical accuracy specifications with economic value assessment.
The presentation scrutinizes the contributory influence of each parameter within the standard HCIIP equation, including specifically Vertical depth, aiming to optimize well survey design whilst taking a balanced approach to accuracy specifications.
Special attention is given to the impact of Vertical depth uncertainty (shown graphically, Fig. 2) on volumetric estimation. By controlling Vertical depth uncertainty to meet specified tolerances, operators can increase recoverable reserves and make more robust business decisions. The differences between the approach discussed and currently used industry standard (ISCWSA) methods is highlighted.
A practical example demonstrates how applying these quantification methods results in both enhanced value of HCIIP calculations as well as creation of greater stakeholder confidence in reserves estimation. This clearly highlights the tangible improvements in HCIIP value achieved through improved management of Vertical depth uncertainty, this specifically in HAHZ wells.
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Workflow For Modeling Expected Responses of Petrophysical Measurements In High-angle Wells Using Geological Understanding To Quantify Impact On Reservoir Evaluation And Structural Definition
Juan Ariza, SLB
Objectives/Scope: The increasing number of high-angle and horizontal wells being drilled through thin reservoirs, formation evaluation has become more complex. Logging measurements in these wells often include contributions from non-reservoir formations located within the depth of investigation. If not properly accounted these "shoulder bed" effects can lead to significantly incorrect interpretations. This work presents a recommended workflow to visualize and model the impact of shoulder beds on logging responses. It allows for interpretation of log responses, estimation of correction magnitudes, and assessment of the resulting impact on petrophysical properties.
Methods, Procedures, Process: A thorough understanding of the geological context, including layering and faults, is essential to evaluate the influence of shoulder beds on log measurements. The process includes defining the formation geometry. Based on this, the initial layer properties are estimated. Forward modeling is then performed using the structural model and estimated layer properties. The synthetic logs generated are compared to actual measurements. Adjustments to the structural model and/or formation properties are made to achieve agreement between modeled and observed log responses.
Results, Observations, Conclusions: Different petrophysical measurements are affected differently by shoulder-bed effects. Modeling was performed for a porous carbonate reservoir adjacent to a dense anhydrite. Two parameters were varied: Thickness of carbonate and distance from the anhydrite. Key findings include: Neutron Porosity: Can be underestimated by up to 80% in extreme cases. Bulk Density: Affected by approximately 5-10%. Resistivity: Severely impacted by shoulder-bed effects, particularly propagation resistivity. Notably: Pseudo-separation patterns may falsely indicate fluid invasion. Apparent resistivity increase by an order of magnitude, leading to incorrect fluid saturation estimates. Total and effective porosity: using density/neutron model total and effective porosity can be underestimated up to 50 %. Lithology identification and quantification: can be significantly impacted by the influence of shoulder-bed effects on nuclear logs, leading to inaccurate interpretations. Permeability estimation and rock typing workflows that rely on lithology and porosity—especially those developed using vertical wells with minimal log distortion—may yield unreliable results when applied wells affected by geometrical effects. This workflow addresses common geometrical effects observed in high angle wells and offers petrophysicists the following benefits: Improved understanding of expected log responses under various geological scenarios, enabling better-informed real-time decisions. Quantitative estimates of the impact on key parameters such as porosity, saturation, permeability, and reservoir storage/flow capacity.
Novel/Additive Information: Due to the challenges in interpreting logs from high-angle wells, many petrophysicists currently limit their use to well placement and reservoir structure definition, overlooking valuable data for reservoir characterization. This workflow enables interpreters to better understand and correct for shoulder-bed effects. As a result, it expands the value of data in development wells, improving the reliability of petrophysical evaluations and reservoir understanding.
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Towards Well Placement Automation; Revolutionizing Geo-steering with Automated Dip Picking from Image and Boundary Mapping from Azimuthal Resistivity Multi-Layer Inversions
Mohamed Fouda, Haliburton
Objectives/Scope
Well placement in thin targets and complex geological structures has long been a challenge for successful well delivery of horizontal wells. Achieving optimal placement in complex reservoirs requires real-time interpretation of subsurface data and continuous adjustments of the well trajectory. Manual geosteering workflows are subjective, consume time and effort and are subject to human error. Recent advancements in artificial intelligence and machine learning (AI/ML) algorithms utilizing LWD images and multi-layer inversion as a critical input for the changes in the structural dip, boundary thickness and dip variations have enabled the automation of several well placement processes making a breakthrough in geosteering capabilities and improving consistency, well placement precision and operational efficiency.
Methods, Procedures, Process
Geosteering processes focusing on real-time interpretation and decision-making using Logging While Drilling (LWD) data include conventional LWD curves used for well correlation and petrophysical analysis as well as more advanced data types such as LWD azimuthal images and deep or ultra-deep resistivity inversions. The automated geosteering workflow includes the handling of all these data types and achieves automated lithology evaluation, well-to-well automated correlation, automated dip picking from azimuthal LWD images, automated geological surface updates as well as automated bed boundary detection derived from advanced deep and ultra-deep resistivity inversions. These developments aim to enhance real-time well placement by streamlining decision-making and reducing dependence on subjective interpretations aimed at ultimately improving operations efficiency
Results, Observations, Conclusions
The automated workflows were successfully implemented to correlate between wells, automatically analyze LWD images for dip determination, replacing manual analysis with faster and more consistent interpretation. Correlation algorithms integrated offset well logs to adjust geological surface interpretation while drilling in real time. Boundary mapping automation utilized deep and ultra-deep resistivity data inversions, enabling the precise identification of distance to bed boundaries. An integrated workflow integrates all these components as well as directly feeds directional drilling automation platforms for accurate and immediate trajectory adjustments. The drilling and Geosteering automated process collectively results in reduced wellbore placement deviations, improved borehole tortuosity, maximized reservoir contact, and significant time savings.
Novelty/Significance/Additive Information
This study introduces a fully automated drilling and geosteering framework that transforms the traditional real-time decision-making process which sets a new standard for the accuracy and efficiency of horizontal well delivery. This is an important step towards fully automated geosteering and drilling automation.
Location
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