Wellbore Logs Research Articles

A Universal Data Format for Wellbore Logs

This paper describes a proposed high-specification standard format that is ideally suited for the data management of definitive records of wellbore logs. For this reason, it is a good standard for data exchange between applications. The format is suitable for complex three-dimensional (3D) data, including those generated by deep azimuthal resistivity (DAR) and ultradeep azimuthal resistivity (UDAR) tools, acoustic borehole reflection images, vertical seismic profiles (VSP), borehole imaging tools, multifingered caliper logs, and array data with multiple depths of investigation. It is applicable for use with logging-while-drilling (LWD) and wireline-conveyed logging tools. The format also naturally collapses down when utilized to store simple conventional logs that contain one value per depth in the wellbore. The proposed format provides spatial details of every data point collected by or interpreted from a wellbore-logging tool. The position of each data point is defined by reference back to the measure point of the sonde, which in turn is defined by the wellbore deviation survey and its coordinate reference system (CRS). Each data point in space may have an unrestricted number of parameters. An example might be most likely horizontal and vertical resistivity, maximum value based on uncertainty, minimum value based on uncertainty, and flags indicating the data position with respect to depth of detection (DOD). The new proposed format is so versatile. It is suitable as an Open Group Open Subsurface Data UniverseTM (OSDUTM) standard to store and exchange all data measured by logging tools in a wellbore and can possibly be extended to include all well data (for example, core, cuttings, and more). The proposed format requires a detailed definition so that computer scientists can implement it in applications used for subsurface modeling. The OSDU will also require this detailed definition in order to adopt it as a standard.

Designs of ultra-HPHT Electrical Component Packages for Downhole and Geothermal Wellbore Logging Tool Integrations

Conventional dielectric sealing materials (PEEK, glass and glass-ceramic) used for sealing electrical feedthroughs, connectors, interconnectors and bulkheads in electronic packages can provide reliable downhole wellbore long-term logging tool service up to 150C or short-term logging service for greater than/equal 200C, due primarily to low glass transition temperature of the used sealing materials. This paper will demonstrate that the maximum allowable operating pressure and temperature could be from 20KSI to 100KSI and from 200C to 400C with Borosilicate and Bismuth-Boron-Silica (XTS) sealing glasses. Borosilicate glass sealed Inconel-Kovar/Kovar electronic housing could maintain reliability up to the maximum pressures of ~35KSI at 200C or 25KSI at 400C. Similarly, a Bismuth-Boron-Silica XTS glass sealed stainless steel electronic package housing could have a maximum operating pressure of ~100KSI at 150C or ~50KSI at 300C temperature. It has been found that high glass transition temperatures of (440-560)C for Borosilicate glass and (44010)C for Bismuth-Boron-Silicate (XTS) glass are key for making highly reliable ultra-HPHT electronic component packages. It is shown that the tetrahedral diamond-like microstructures of these sealing glasses are keys to ensure water-repelling properties to maintain sufficient electrical insulation resistance regardless of their use in water or moisture-rich wellbores. Moreover, compressive pin stress is found to be additional key for mitigate frequently observed glass seal cracks during logging tool field services.

Comparative Study of Machine-Learning-Based Methods for Log Prediction

Improving data quality during log preprocessing is an important task that can consume most of the time of the petrophysicist, with a high impact on the final interpretation. As part of the initiative to increase automation and homogeneity in the data completeness of logs in a field, we organized a systematic comparison of multiple regression models that provided successful predictions of wellbore logs. These approaches can be potentially valuable when extrapolating measurements available on a few wells to a more extensive set of wellbores, predicting low-quality data intervals, and increasing the availability of complete data sets. This study aims to compare the performance of three promising machine-learning (ML) methods when predicting one of the following curves: density, neutron porosity, and compressional slowness curves. We view the need to evaluate models that could provide answers even in the presence of multiple missing logs or logs with alteration, which is a common scenario in petrophysics. Because of that, we built a comparison based on three ML methods that can handle those issues: window-based convolutional neural network autoencoder (WAE), pointwise fully connected autoencoder (PAE), and eXtreme Gradient Boosting (XGBoost). We developed the PAE and WAE methods to handle challenging scenarios of interest, and we used the original implementation of XGBoost, which is already built to handle missing values. We compare the computational complexity, prediction errors [root mean square error (RMSE) and mean absolute error (MAE)], Pearson’s correlation, peak signal-to-noise ratio (PSNR), and the visual analysis of both high- and low-scale feature reconstruction, conducting the comparison in two field data sets. We also used the same methods to predict photoelectric factors and interpreted formation properties such as total organic content in multiple field data sets.

Deep Learning for Multiwell Automatic Log Correction

Researchers have dedicated numerous applications of machine-learning (ML) techniques for fi eld-scale automated interpretation of well-log data. A critical prerequisite for automatic log processing is to ensure that the log characteristics are reasonably consistent across multiple wells. Manually correcting logs for consistency is laborious, subjective, and error prone. For some wellbore logs, such as gamma ray and neutron porosity, borehole effects and miscalibration can cause systematic inconsistencies or errors that might be present even after the application of wellbore and environmental corrections. Biased or consistently inaccurate data in the logs can confound ML approaches into learning erroneous relationships, leading to misinterpretations, such as wrong lithology prediction, reservoir estimation, and incorrect formation markers. To overcome such difficulties, we have developed a deep learning method to provide petrophysicists with a set of consistent logs through the multiwell automatic log correction (MALC) workflow. Presently, the corrections we target are systematic errors on the standard logs, especially gamma ray and neutron logs, random noises, and to a lesser extent, local formation property misreading due to washouts. We applied the proposed method in multiple fi elds worldwide containing different challenges, and in this paper, we include the results in two fi eld examples. The first one covers the correction of synthetic coherent noise added to fi eld data, and the second example covers the correction applied to original measurements.

Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms

Shear wave velocity (VS) data from sedimentary rock sequences is a prerequisite for implementing most mathematical models of petroleum engineering geomechanics. Extracting such data by analyzing finite reservoir rock cores is very costly and limited. The high cost of sonic dipole advanced wellbore logging service and its implementation in a few wells of a field has placed many limitations on geomechanical modeling. On the other hand, shear wave velocity VS tends to be nonlinearly related to many of its influencing variables, making empirical correlations unreliable for its prediction. Hybrid machine learning (HML) algorithms are well suited to improving predictions of such variables. Recent advances in deep learning (DL) algorithms suggest that they too should be useful for predicting VS for large gas and oil field datasets but this has yet to be verified. In this study, 6622 data records from two wells in the giant Iranian Marun oil field (MN#163 and MN#225) are used to train HML and DL algorithms. 2072 independent data records from another well (MN#179) are used to verify the VS prediction performance based on eight well-log-derived influencing variables. Input variables are standard full-set recorded parameters in conventional oil and gas well logging data available in most older wells. DL predicts VS for the supervised validation subset with a root mean squared error (RMSE) of 0.055 km/s and coefficient of determination (R2) of 0.9729. It achieves similar prediction accuracy when applied to an unseen dataset. By comparing the VS prediction performance results, it is apparent that the DL convolutional neural network model slightly outperforms the HML algorithms tested. Both DL and HLM models substantially outperform five commonly used empirical relationships for calculating VS from Vp relationships when applied to the Marun Field dataset. Concerns regarding the model's integrity and reproducibility were also addressed by evaluating it on data from another well in the field. The findings of this study can lead to the development of knowledge of production patterns and sustainability of oil reservoirs and the prevention of enormous damage related to geomechanics through a better understanding of wellbore instability and casing collapse problems.Graphical abstract

Robust determination of kerogen properties in organic-rich mudrocks via Raman Spectroscopy

Organic-rich mudrocks are an expansive resource of hydrocarbons that support the global energy demand. Effective characterization and appraisal of these resources relies upon accurate volumetric quantification of organic phases in the formation, which include producible hydrocarbons (oil and gas) and an abundant, nonproducible, insoluble solid (kerogen). A substantial uncertainty in this volumetric quantification comes from the variable, and nearly always unknown, composition and properties of kerogen. This paper demonstrates a novel method to quantify relevant properties of type II kerogen in organic-rich mudrocks from Raman spectroscopy measurements of bulk samples. The correlations are developed using a geographically and geologically diverse set of organic-rich mudrocks containing type II kerogens, with ages spanning more than 200 Ma and hydrocarbon generation stages ranging from immature to dry gas. The properties comprise kerogen’s carbon mass fraction, density, hydrogen index, apparent thermal neutron porosity, and macroscopic cross section for thermal neutron capture. These properties are estimated from empirical correlations between these kerogen property values quantified by laboratory reference techniques and kerogen spectral characteristics quantified from Raman measurements. The Raman-based method is a practical alternative for quantification of kerogen properties that are critical for the correct interpretation of common wellbore logging measurements made in organic-rich mudrocks.

High-Resolution Wellbore Tortuosity Logs Improve Completion and Production Equipment Placement

Wellbore tortuosity is a term that has steadily increased in relevance to the oil and gas industry over the past decade, but its importance is especially clear in the current environment. The convergence of several major global events - the ongoing COVID-19 pandemic and persistent weakness in commodity pricing - combined with the industry’s general attitude toward rate of penetration as the performance driver is leading to wells of inferior quality being drilled. The issue of wellbore quality is exacerbated by the division among drilling, completions, and production as functional disciplines, leading to dramatically different objectives and methods of quantifying success in each project phase. In wells with high tortuosity, the drilling process and drilling efficiency are affected, as well as the effectiveness of the completions and production equipment in achieving reservoir return rates. Defining wellbore tortuosity in relevant areas, such as openhole wellbores, production tubing, or casing, is often a very difficult task; historically, it has been a technical area fraught with challenges and misunderstandings. Though metrics designed to analyze wellbore tortuosity were developed in the past several decades, these generally relied on using the calculated dogleg of the wellbore every 95 ft. While such technologies were used with limited success, the received information lacked the precision and granularity necessary to explain the true difficulties of running and operating equipment in the well. Innovation was necessary. One such innovation is a system from Gyrodata that generates wellbore tortuosity logs in conjunction with a gyroscopic surveying tool or with another service that provides comparable data. The system defines reference lines for the wellbore path based on survey data and determines displacements of the wellbore path from the reference lines. Through a series of calculations based on this information, the wellbore shape can be represented and visualized in 3D, allowing an operator to make critical decisions on well development and placement for artificial lift and other equipment in line with areas of low tortuosity. By collecting high-resolution data at 1-ft intervals vs. the standard stand-length intervals of measurement-while-drilling (MWD) tools, the technology reveals areas of high sideloading forces and high friction that would otherwise be invisible. This allows improved rod-guide placement, reducing or eliminating casing (tubing) damage and necessary workovers. Also, the technology allows identification of areas of low tortuosity, thereby reducing premature failures, increasing equipment life, and mitigating cable damage while setting the electrical submersible pump (ESP).

Evaluation of Mineralogy per Geological Layers by Approximate Bayesian Computation

Summary We propose a new three-step methodology to perform an automated mineralogical inversion from wellbore logs. The approach is derived from a Bayesian linear-regression model with no prior knowledge of the mineral composition of the rock. The first step makes use of approximate Bayesian computation (ABC) for each depth sample to evaluate all the possible mineral proportions that are consistent with the measured log responses. The second step gathers these candidates for a given stratum and computes through a density-based clustering algorithm the most probable mineralogical compositions. Finally, for each stratum and for the most probable combinations, a mineralogical inversion is performed with an associated confidence estimate. The advantage of this approach is to explore all possible mineralogy hypotheses that match the wellbore data. This pipeline is tested on both synthetic and real data sets.

Groundwater study in Subang Industrial park and its recharge area as a suggestion for establishing recharge and discharge zones of Subang Groundwater Basin

This research was conducted in Subang Groundwater Basin, West-Java, related to the prohibition of groundwater extraction in the Subang Industrial Park (SIP) area. This is because the area is considered as the Recharge Zone of the groundwater basin. The purpose of this study is to determine whether SIP stands above the Recharge Zone or not, moreover, find out which part of the Basin that supplies groundwater aquifers of SIP. The method used in this study is applied of DRASTIC method using ArcGIS and conducting field research measuring the infiltration rate of soil formations at selected points in the Basin, geologic and hydrogeological mapping of Lakes. The results of this study indicate that the SIP is indeed built on a recharge area, the soil where the SIP is established, has ability to infiltrate rainwater. However, the results of more detailed observations of wellbore logs in this area, it is known that between the groundwater aquifer used in SIP and the infiltration zone of the ground surface is separated by impermeable clay layers. This ensures that there is no relationship between surface water infiltration and groundwater being extracted by factories in the areas. Therefore, it is certain that the recharge area originates from other areas in the Basin. Key words: aquifer, recharge area, Subang Groundwater Basin.

Numerical modeling for drilling fluid invasion into hydrate-bearing sediments and effects of permeability

Drilling fluid invasion into hydrate-bearing sediments could induce hydrate dissociation and complicate heat and mass transfer around wellbore, and further affect mechanical strength of hydrate-bearing sediments and accurateness of wellbore logging interpretations. In this study, a cylindrical numerical model was established to study the characteristics of drilling fluid invasion into hydrate-bearing sediments and the effects of permeability on this process. The distributions of temperature, pressure, saturation, and salinity of pore water around wellbore at different time were obtained. The pressure and temperature around wellbore gradually increase, and the hydrate around wellbore dissociates with the high-temperature drilling fluid invasion. Meantime, water and gas generated from hydrate dissociation gradually migrate outward and then form ‘secondary hydrate’ in some areas outside wellbore. Dissociation and formation of hydrate can sharply change the salinity of pore water around wellbore. The drilling fluid invasion and hydrate dissociation ranges become larger when the intrinsic permeability is higher. The salinity in sediments decreases sharply while the dilution range is narrow when drilling fluid invasion into hydrate-bearing sediments with low permeability. In addition, the permeability decline exponent of the Masuda model has a significant influence on drilling fluid invasion. However, the Corey exponents of the relative permeability model only have a limited influence on drilling fluid invasion into hydrate-bearing sediments with low intrinsic permeability (e.g., 5.5 mD), while they have a noticeable influence on hydrate-bearing sediments with high intrinsic permeability (e.g., 75 mD).

A predictive filtration model considering mudcake compressibility and non-uniform properties’ profiles

Mudcake buildup has a direct impact on expensive drilling and production problems, such as wellbore instability, pipe sticking, formation damage, and impairment of wellbore logging interpretation. Therefore, a better understanding of filtration and mudcake buildup is very valuable. This paper presents a predictive filtration model that accounts for the mudcake compressibility and captures non-uniform filtercake properties profiles. The model solves for the effective stresses acting across the mudcake thickness, based on which mudcake properties profiles are calculated. The mudcake is modeled as a stack of thin sub-layers, with each having its own properties. The porosity and permeability relations with effective stress are determined using the Odometer test, which is analyzed based on Terzaghi's theory for 1D consolidation. A detailed derivation of the model's equations is presented. Also, a computationally efficient pseudo-code solving the model's equations is suggested. Finally, the derived model is validated using experimental filtration results.

РЕГИОНАЛЬНОЕ ЗНАЧЕНИЕ И ОБЪЕМЫ ПЕРЕРЫВОВ/НЕСОГЛАСИЙ В ПАЛЕОГЕНОВЫХ ОТЛОЖЕНИЯХ СЕВЕРНОЙ ТЕТИЧЕСКОЙ ОБЛАСТИ

РЕГИОНАЛЬНОЕ ЗНАЧЕНИЕ И ОБЪЕМЫ ПЕРЕРЫВОВ/НЕСОГЛАСИЙ В ПАЛЕОГЕНОВЫХ ОТЛОЖЕНИЯХ СЕВЕРНОЙ ТЕТИЧЕСКОЙ ОБЛАСТИ

Numerical Simulation of Hydraulic Frac-turing Process for an Iranian Gas Field in the Persian Gulf

Most of the Iranian oil and gas wells in the Persian Gulf region are producing through their natural productivity and, in the near future, the use of stimulation methods will be undoubtedly necessary. Hydraulic fracturing as a popular technique can be a stimulation candidate. Due to the absence of adequate research in this field, numerical simulation can be an appropriate method to investigate the effectiveness of hydraulic fracturing. In the current study, the hydraulic fracturing process is simulated for a wellbore in the Persian Gulf region with Abaqus software. The main parameters that are necessary for the simulation are collected through wellbore logs and core tests. Fracturing process is studied with more emphasis on the pressure of fracturing fluid and fracture opening. Finally, several 3D fluid-solid coupling finite element models are generated and the main obtained results are compared.

Spatial-temporal pattern recognition of groundwater head variations for recharge zone identification

The delineation of groundwater recharge zones is crucial for the conservation of groundwater quality and quantity. To objectively estimate groundwater recharge zones, many field surveys are required that are costly in both time and money. To facilitate the assessment of recharge zones with high efficiency and low expense, this study proposes a ‘fast-filter’ approach based on empirical orthogonal function analysis and applies it in a synthetic case study and to Taiwan’s Yilan Plain. In the synthetic case study, we demonstrate that the proposed method can effectively identify the recharge area by considering the head variations driven by rainfall recharge. For the case of Yilan Plain application, the field investigations (i.e., collected wellbore logs and electrical resistivity tomography [ERT] surveys) and a groundwater simulation model support the recharge zones estimated by the proposed method. The study results show that within the estimated recharge zone, all of the collected wellbore logs consist of coarse grains, and thick and continuous high resistivity zones were shown in the ERT profile images. Moreover, the groundwater model indicates that the recharge within the estimated recharge zone is 57.6% of the total recharge despite that the area of the estimated zone is only 26.8% of the study area. Therefore, the proposed method is shown to delineate recharge zones at low cost.

Results from Newberry Volcano EGS Demonstration, 2010–2014

The Newberry Volcano EGS Demonstration is a 5 year field project designed to demonstrate recent technological advances for engineered geothermal systems (EGS) development. Advances in reservoir stimulation, diverter, and monitoring are being tested in a hot (>300°C), dry well (NWG 55-29) drilled in 2008. These technologies could significantly reduce the cost of electrical power generation from geothermal resources. The project, funded in part by the Department of Energy, began in 2010 with two years of permitting, technical planning, and development of a project-specific Induced Seismicity Mitigation Plan (ISMP). Well stimulation carried out in 2012 indicated that casing repairs were needed; confirmed by further wellbore logging and analysis in 2013. Repairs were completed in August 2014, and the well was re-stimulated in the fall. 9500m3 (2.5 million gallons) of groundwater were injected at a maximum wellhead pressure of 195bar (2850 psi) over 4 weeks of hydraulic stimulation. Injectivity changes, thermal profiles and seismicity indicate that fracture permeability in well NWG 55-29 was enhanced. The fifteen-station microseismic array (MSA) located 398 events in 2014, ranging in magnitude from M 0 to M 2.26. Temperature logs run after injection of thermally-degradable zonal isolation material (TZIM) showed that at least two flow zones were blocked and one or two new zones opened because of the injected TZIM. Break-down products of TZIM were detected in flow-back fluids, indicating that the material degraded as predicted. This work demonstrates the viability of large-volume low-pressure stimulation coupled with non-mechanical diverter technology and microseismic monitoring for reservoir mapping.

Defining structural permeability in Australian sedimentary basins

Declining conventional hydrocarbon reserves have triggered exploration towards unconventional energy, such as CSG, shale gas and enhanced geothermal systems. Unconventional play viability is often heavily dependent on the presence of secondary permeability in the form of interconnected natural fracture networks that commonly exert a prime control over permeability due to low primary permeabiliy of in situ rock units. Structural permeability in the Northern Perth, SA Otway, and Northern Carnarvon basins is characterised using an integrated geophysical and geological approach combining wellbore logs, seismic attribute analysis and detailed structural geology. Integration of these methods allows for the identification of faults and fractures across a range of scales (millimetre to kilometre), providing crucial permeability information. New stress orientation data is also interpreted, allowing for stress-based predictions of fracture reactivation. Otway Basin core shows open fractures are rarer than image logs indicate; this is due to the presence of fracture-filling siderite, an electrically conductive cement that may cause fractures to appear hydraulically conductive in image logs. Although the majority of fractures detected are favourably oriented for reactivation under in situ stresses, fracture fill primarily controls which fractures are open, demonstrating that lithological data is often essential for understanding potential structural permeability networks. The Carnarvon Basin is shown to host distinct variations in fracture orientation attributable to the in situ stress regime, regional tectonic development and local structure. A detailed understanding of the structural development, from regional-scale (hundreds of kilometres) down to local-scale (kilometres), is demonstrated to be of importance when attempting to understand structural permeability.

Multiphysics modeling of CO2 sequestration in a faulted saline formation in Italy

The present work describes the results of a modeling study addressing the geological sequestration of carbon dioxide (CO2) in an offshore multi-compartment reservoir located in Italy. The study is part of a large scale project aimed at implementing carbon capture and storage (CCS) technology in a power plant in Italy within the framework of the European Energy Programme for Recovery (EEPR). The processes modeled include multiphase flow and geomechanical effects occurring in the storage formation and the sealing layers, along with near wellbore effects, fault/thrust reactivation and land surface stability, for a CO2 injection rate of 1×106ton/a. Based on an accurate reproduction of the three-dimensional geological setting of the selected structure, two scenarios are discussed depending on a different distribution of the petrophysical properties of the formation used for injection, namely porosity and permeability. The numerical results help clarify the importance of: (i) facies models at the reservoir scale, properly conditioned on wellbore logs, in assessing the CO2 storage capacity; (ii) coupled wellbore-reservoir flow in allocating injection fluxes among permeable levels; and (iii) geomechanical processes, especially shear failure, in constraining the sustainable pressure buildup of a faulted reservoir.

Collection of baseline wellbore cement data in multiple wells in the same field

Abstract Abandoned wellbores may pose an important risk to the integrity of CO 2 storage formations that have large numbers of existing wells and that risk needs to be better understood. Field and laboratory studies have shown that well cement can be affected by CO 2 at differing levels depending on conditions. However, none of this work has looked at the initial conditions of the well (prior to CO 2 exposure). Understanding the initial conditions will be important for ensuring that the potential risk of leakage from the storage formation is acceptable. The collection of baseline wellbore integrity data allows for comparison during a project and will also identify any potentially problematic wells before a leak may occur. New field data from wells must be used to begin to understand if there are field-wide similarities between existing wells and how the similarities may be used to assess field-wide leakage risk. Existing data are not sufficiently focused (multiple wells in the same field) and there has been no satisfactory method of accelerating laboratory experiments to create realistic wellbore leakage conditions. Similarities between wells in the same fields were examined as part of a project to study the baseline condition and leakage risk of existing wells. Five wells were analyzed. The wells were split between two fields in the state of Wyoming, USA. The investigation used a combination of wellbore logging and sampling tools to analyze well conditions. Logging tools were selected to provide the maximum information on the materials that were used to construct wells and provide zonal isolation. The logging suite included sonic mapping tools, ultrasonic mapping tools, dynamic testers, and sidewall coring tools. Initial results show that there are similarities between wells within the same fields.

Monitoring and Modelling in Coupled Geomechanics Processes

Abstract Geomechanics issues are vital in all reservoir processes, but particularly so in weak, unconsolidated sandstones. Coupled stress-flow simulation is necessary to analyze and understand effects such as changes in reservoir volume that arise from heating and pressurization. Also, non-linear plasticity models incorporating shear dilatancy are needed to simulate the dilation effects that are observed in thermal extraction processes in unconsolidated sands. Stress-flow coupling is based on the volume changes that arise with pressure and temperature changes (?p, ?T). Incorporating shear dilation is based on computation of effective stresses from ?T and ?p, then assessing the state of the rock to see if it is shearing and by how much it must dilate. These processes are poorly quantified at present, so it is necessary to monitor the process to calibrate simulation models. The two monitoring domains of greatest interest to coupled geomechanics simulation are the deformation field and the seismic attributes field. How these fields evolve in space and with time are the key factors to tracking processes, to calibrate geomechanics models and to successfully optimize complex in situ processes. A general geomechanics view of how to achieve process monitoring and optimization goals is presented here. Though recent developments have been promising, further progress in monitoring, inversion and coupled geomechanics simulation is needed. Introduction Conventional monitoring in petroleum engineering addresses pressure, temperature and rate measurements, as well as data collected by wellbore logs such as temperature or rate surveys (e.g. spinner surveys). Oil, gas and water production and injection rates are required for regulatory purposes and to help calculate saturations and recovery factors (RF). Changes in reservoir response were commonly assessed using classical well tests and analyses(1, 2). Because classic reservoir simulation in conventional low viscosity cases deals only with mass and heat transport (Darcy and Fourier diffusion processes) combined with saturation changes and relative permeability calculations, these measures were deemed sufficient for reservoir management. Flow rates (Q), well test data and facilities capability analyses are also used for production optimization(3). These measures are considered insufficient for heavy oil (HO) thermal extraction, HPHT reservoir management, high compaction cases and gravitationally-dominated production technologies. In such cases, we are more interested in measures such as the reservoir pore volume change (?V), gas saturation changes in situ (?Sg), swept volume distribution, and so on. These cannot be measured by conventional p-T-Q methods or geophysical wellbore logging, nor are they easily amenable to calculation. When shear dilation, compaction or induced fracturing take place, major changes in rock mass properties occur; understanding what is happening and where it is taking place requires different monitoring and simulation methods. To make monitoring data more useful, flow-stress coupled modelling, also referred to as coupled geomechanical modelling, is carried out. Changes in p and T are analyzed in terms of effective stress changes (? s'ij) through their effect on rock and pore volumes. The links between ?V and the changes ?p, ?T and ? s'ij are established through p-, T-, s'-compressibilities of the bulk rock and of the mineral matter comprising the matrix.

An On-Campus Well Field for Hydrogeophysics Education and Undergraduate Research

The emerging subdiscipline of hydrogeophysics is underdeveloped in undergraduate curricula relative to its importance in professional engineering/environmental practice. In 2001, the Bucknell Department of Geology initiated efforts to refocus an undergraduate geophysics course on near-surface geophysical methods for hydrologic, environmental, and engineering problems. In addition to offering students practical experience, treatment of hydrogeophysics provides important pedagogical opportunities. Field-based hydrogeophysics labs challenge students to integrate concepts from other geology courses, as well as from physics, math, and chemistry.We faced two challenges in revising our geophysics course: (1) access to wells for field exercises on borehole geophysics; and (2) the costs of acquiring and maintaining equipment. We pursued two strategies to solve these problems. First, we established an on-campus well field, which serves as a field laboratory for downhole and cross-hole experiments. Second, we incorporated field demonstrations and lectures by professional geoscientists, including alumni, into our courses. By adding field exercises to our syllabi and promoting undergraduate research, we are building a cutting-edge dataset that includes televiewer and standard wellbore logging, cross-hole tomography, and hydraulic-test data. Student-led analysis of these data has already provided valuable insights into the control of fractures on aquifer properties, and these observations are being combined with outcrop studies to place our results in a more regional context.