Borehole Image Research Articles

Review of discrete fracture network characterization for geothermal energy extraction

Geothermal reservoirs are highly anisotropic and heterogeneous, and thus require a variety of structural geology, geomechanical, remote sensing, geophysical and hydraulic techniques to inform Discrete Fracture Network flow models. Following the Paris Agreement on reduction of carbon emissions, such reservoirs have received more attention and new techniques that support Discrete Fracture Network models were developed. A comprehensive review is therefore needed to merge innovative and traditional technical approaches into a coherent framework to enhance the extraction of geothermal energy from the deep subsurface. Traditionally, statistics extracted from structural scanlines and unmanned aerial vehicle surveys on analogues represent optimum ways to constrain the length of joints, bedding planes, and faults, thereby generating a model of the network of fractures. Combining borehole images with seismic attributes has also proven to be an excellent approach that supports the stochastic generation of Discrete Fracture Network models by detecting the orientation, density, and dominant trends of the fractures in the reservoirs. However, to move forward to flow modelling, computation of transmissivities from pumping tests, and the determination of hydraulically active fractures allow the computation of the hydraulic aperture in permeable sedimentary rocks. The latter parameter is fundamental to simulating flow in a network of discrete fractures. The mechanical aperture can also be estimated based on the characterization of geomechanical parameters (Poisson’s ratio, and Young’s modulus) in Hot Dry Rocks of igneous-metamorphic origin. Compared with previous review studies, this paper will be the first to describe all the geological and hydro-geophysical techniques that inform Discrete Fracture Network development in geothermal frameworks. We therefore envisage that this paper represents a useful and holistic guide for future projects on preparing DFN models.

Assessment of Fracture Density Distribution from Image Logs for Sensitivity Analysis in the Asmari Fractured Reservoir

Characterizing fracture properties in naturally fractured reservoirs poses a significant challenge. While welltesting remains valuable, it often fails to provide precise descriptions of these properties. Bridging this gap requires the integration of geological expertise to enhance fracture assessment. This study addresses the limitations of well-test analysis and explores the application of Conventional Image Logs in structural, fracture, and geomechanical analysis. However, effectively combining these applications with well-test analysis on a field scale reveals a substantial knowledge gap. A critical challenge in this context is the absence of a defined procedure for calculating the variable "σ," a crucial parameter for simulating fractured carbonate reservoirs using image log fracture density. Integrating geological knowledge is essential to reduce uncertainties associated with well-test analysis and provide more accurate characterizations of fracture properties. Image log data processing emerges as a valuable avenue for gaining insights into the static attributes of naturally fractured reservoirs. This study focuses on Characterizing fractures using data from ten image logs and Developing a more accurate simulation model through the interpretation of images, with a particular emphasis on OBM imaging. The main goals of this fracture study revolve around establishing correlations between fracture densities well by well within the simulation and enhancing the accuracy of the simulation model by incorporating fracture data from image logs. Borehole imaging tools such as FMI/FMS and OBMI-UBI play a pivotal role in identifying significant structural features, including faults, fractures, and bedding. Fine-tuning fracture parameters during the history matching process, while potentially time-consuming, significantly impacts other historical match parameters. Consequently, the reliability of reservoir simulation results, predictions, and recovery enhancement strategies hinges on the precision of fracture properties and their distribution within the model. Recent advances in interpretation techniques have expanded the horizons of image interpretation, enabling the creation of more accurate simulation models for fractured reservoirs using fracture data obtained from image logs. The overarching goal of this project is to comprehensively evaluate a fractured reservoir field by integrating data from ten individual wells.

Discontinuity characterization of rock strata using borehole wall imagery and scanline

Rock discontinuity mapping techniques, such as scanlines on slopes or exposed vertical surfaces, can collect data on discontinuity characteristics required to assess the rock’s stability. When slope conditions are highly weathered, or it is challenging to identify discontinuity characteristics using a scanline mapping survey, other methods must be used to obtain this information. One of them employs borehole wall acoustic imaging. This method is sophisticated, fast, and accurate for getting discontinuity characteristic data, but it has a disadvantage in that it requires preliminary drilling work. This issue can be solved if it is done in conjunction with the work of exploration or geotechnical drilling. This study aims to compare the discontinuity characterization data recorded using borehole wall acoustic imaging and scanline methods by considering the advantages and disadvantages of both approaches. The characterization data is essential for assessing rock mass quality. When these two methods are combined in mining activities, they will provide added value by utilizing the right technology and ensuring high accuracy while following good mining practices.

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.

Application of GAN to Resolution Enhancement of LWD Real-Time Image Logs to Support Decision Making

In the current scenario of project management, where the agility and optimization of operations have been prioritized, the practice of logging while drilling (LWD) has gained space compared to traditional wireline logging. In theory, acquiring quality petrophysical properties during drilling brings greater agility in decision making about completion and optimizes operation costs. However, regarding borehole image logs, due to limitations in transmission capacity, the actual available data in real time contain about 50% (for resistivity images) of the full azimuth information, being insufficient for the identification of critical geological structures capable of impacting the communication between production or injection zones or the quality of cementation, such as fractures, caves, and geomechanical collapse zones. The tool’s memory data with the full information may take a few days after the end of drilling to be delivered by the service company, which in some cases is not enough for fast decision making regarding completion. In this work, we tested models based on generative adversarial neural networks (GANs) to reconstruct the complete memory data based on real-time input. As in conventional GAN schemes, a generator is trained to receive a real-time input and create a “memory-like” image, while a discriminator is trained to tell real and fake images apart. To regularize the convergence of training, we used an architecture known in the literature as CycleGAN, where another generator-discriminator pair is trained simultaneously to do the reverse process, recreating the real-time data. Variations of the training process and data sets were used to generate different CycleGAN models. They were trained using logs of presalt reservoirs in Buzios Field, and performance was assessed on logging intervals not seen by the algorithms during training. The results achieved so far have been very promising, as in certain intervals, resultant models were able to capture the presence of fractures and caves. This methodology represents a way of circumventing telemetry limitations, where missing information is added indirectly to the real-time data as the artificial intelligence (AI) algorithm learns the main characteristics of a field/reservoir. Therefore, previous knowledge from the field can be used to continuously optimize future operations, efficiently incorporating the available database into the workflow of petrophysicists for the recognition of geological and geomechanical structures in time to support decision making in completion operations.

New insights into hypogenic non-matrix dissolution mega features driving subsurface fluid movement within the Arab Formation, Saudi Arabia

This paper reports the results of a large integrated study into the classification, distribution and significance of hypogenic non-matrix large-scale dissolution features present in the Arab Formation of Saudi Arabia. The investigation of these features was based primarily on extensive core, wireline caliper, wireline/log while drilling resistivity borehole image logs supported by encountered total lost circulation of drilling fluids and production log data. Dissolution features observed by this study were classified into three main categories: touching vugs, ramiform voids, and cavities. This study is the first to successfully quantify the presence and extent of these non-matrix intervals in this formation, which has greatly improved the 3D modelling efforts. Over 8100 feet of large-scale dissolution features were intersected in both vertical and horizontal wells. The hypogenic genesis of the large-scale dissolution features pre-dates replacement dolomitization in the area. Given the extensive data reviewed, the presented results give insight into the importance of the large-scale dissolution mega features as they are strongly related to total loss of mud circulation during drilling, and will have implications for well-to-well short-cutting during production and impact oil storage capacity.

Application of percentile color intensities of borehole images for automatic fluorite grade assessment

This paper describes a practical application of support vector machine (SVM) for ore grading in an underground fluorite mine. It covers all aspects from the inception of the experiments, data collection, input preparation, model description and results. Forty-eight drilling chips samples are collected while drilling six pseudo-horizontal boreholes at depth intervals of half a meter and their chemical composition determined through X-Ray fluorescence; the response of the drill rig is used to accurately define the depth of each sample along the blasthole. Images of the blasthole walls are collected with an optical televiewer with white and ultraviolet (UV) illumination. The color information of the images is characterized by the cumulative distribution of pixel color intensities of red, green and blue, used as inputs. A well-known metaheuristic algorithm is used to calibrate the SVM hyperparameters. Repeated k-fold cross validation is applied to increase the prediction performance due to the small-size of the dataset. An outlier inspection is made resulting in improved performance. The combination of pixel intensities from white and UV light scans leads to the best prediction of fluorite content (average R2 = 0.83 and RMSE = 3.32 %), while intensities from only white light procures the best classification results (average classification accuracies from 0.77 to 1). These metrics support the utility of the proposed methodology for reducing the amount of lab analysis in ore grade control.

Fracturing timing of Jurassic reservoirs in the Dibei-Tuziluoke gas field, Kuqa foreland basin: Evidence from petrography, fluid inclusions, and clumped isotopes

Determining the timing of fracturing is crucial for understanding reservoir evolution and hydrocarbon accumulation in foreland basins. Using fracturing data from cores, borehole images, and outcrops, combined with the clumped isotope (Δ47) and fluid inclusion analyses of carbonate minerals filled in pores and fractures, this study ascertained the fracturing timing of the Jurassic reservoirs in the Dibei-Tuziluoke Gas Field, Kuqa Foreland Basin. Data from outcrops and borehole images show two dominant fracture sets in the study area: W-E and NE-SW striking fractures. Some W-E striking fractures are carbonate-filled, while NE-SW striking fractures lack mineral fillings. Bitumen veins, not easy to be identified in borehole images, are prevalent in cores. The petrographic analysis reveals that these bitumen veins formed before the calcite cementation in pores and display high viscosity and low maturity. Homogenization temperatures (Th) from primary fluid inclusion assemblages in two representative calcite vein samples were notably lower than TΔ47 values from corresponding samples. This suggests the Δ47 signature underwent alteration due to partial reordering during burial. Thus, Δ47-derived temperatures (apparent temperatures) may not faithfully represent the mineral precipitation temperatures. When plotting these apparent temperatures vs. the burial history, only the possible latest ages of fracturing emerged. These ages were further refined by considering petroleum charging, tectonic evolution, and stress orientation. Bitumen-filled fractures likely resulted from the Late Cretaceous uplift, marking the migration of low-maturity hydrocarbons in the study area. Carbonate-filled E-W striking fractures emerged during the late Miocene (∼13–6.5 Ma) alongside fold development. NE-striking fractures that crosscut W-E ones possibly formed recently due to stress reorientation.

Curvature analysis and its correlation with faults and fractures in presalt carbonates, Santos Basin, Brazil

Presalt lacustrine carbonate reservoirs in the Santos Basin, Brazil, can have a high degree of fracturing. Properly characterizing such properties is important due to their influence on the porosity–permeability system. It may play a key role in the so-called excess permeability features and the flow behaviour, especially in the Aptian Alagoas Stage. Therefore, 3D characterization of the fracture system improves the reservoir model. For this purpose, correctly identifying the fault and fracture zones in seismic data is crucial. This task is generally performed manually and guided by amplitude interpretation or geometric seismic attributes. However, due to the seismic resolution of the pre-salt seismic datasets, many faults and fractured zones are not identified in the seismic amplitude domain or by standard geometric attributes such as coherence. Improving the resolution of seismic data and its geometric attributes can positively impact the delineation of fractured zones, structural lineaments, and their connectivity. Curvature (k) attributes have a high potential to reveal vertical to subvertical subseismic-scale structures, which is the main type of strain generated from the tectonic style in the Pre-salt rocks. Among the curvature attributes, the most-positive (k1) and the most-negative (k2) attributes are some of the most commonly used. The present study evaluates the use of seismic inverse Q-filter and three different dip estimation techniques based on Fast Fourier Transform (FFT), Principal Component Analysis (PCA), and Phase Gradient (PG). It also adds two postfiltering techniques (median and recursive Gaussian filters) to obtain a consistent most-positive curvature. We then analyse two analytical models that correlate the volumetric fracture intensity, measured on Borehole Image Logs (BHI), with the curvature. Then, we perform a comprehensive study to understand the role of seismic-scale strain (translated into curvature) and mechanical stratigraphy in the development of fractures in the presalt, where we address that in addition to seismic-scale deformation, the contents of silica, clay, and organic matter are also relevant variables. These results can help to guide future studies of fracture characterization to prospect naturally fractured reservoirs or to estimate fracture intensity for dual-porosity reservoir modelling on the Santos presalt carbonates.

Formation of natural fractures and their impact on shale oil accumulation in the Mahu Sag, Junggar Basin, NW China

Lacustrine shale oil reservoirs of the Fengcheng Formation in the Mahu Sag, Junggar Bain, NW China contain abundant oil resources, with the highest daily oil production of a single well reaching over 700 barrels. Based on core and thin section observation along with borehole image interpretation, this study integrated paleotectonic stress regime, fluid inclusion analysis, and calcite UPb dating to clarify fracturing periods and discuss the influence of fractures on shale oil accumulation. Results show that natural opening-mode fractures are widespread in the Fengcheng Formation, which play an important role in oil accumulation. Fractures are developed in several stages and filled by three minerals: reedmergnerite, quartz and calcite. Reedmergnerite and quartz fillings show similar fluid inclusions and petrographic features, with numerous hydrocarbon inclusions compared to aqueous ones, yet, such inclusions were less observed in calcite fillings. Fractures in the study area were formed in two separate stages. In the first period, due to the NW-SE compression of the Hercynian movement, the WNW-ESE and NNW-SSE striking fractures were formed in the Late Permian, with Th values of 95–115 °C. The first stage of fractures coincided with hydrocarbon generation, providing migration pathways for the oil. In the second period, due to the nearly SN compression of the Indosinian movement, the NNW-SSE and NNE-SSW striking fractures were formed in the late Triassic, with Th values of 120–140 °C. The second stage of fractures was formed subsequent to major hydrocarbon generation and expulsion period, hence their contribution to hydrocarbon migration and accumulation was found relatively minor. Moreover, fractures with the nearly E-W, ENE-WSW and WNW-ESE strikes intersect with the present-day maximum horizontal principal stress at a small angle, with large apertures and good connectivity, which should have a positive impact on shale oil accumulation.

Study on Mechanism of Cumulative Directional Blasting of Brittle Karst Limestone in the Guizhou Province

The theoretical analysis, mechanical test, numerical simulations, and model tests are carried out on the Taoziya tunnel in Guizhou to investigate the influence law of cumulative blasting technology on directional rock breaking and fracture propagation of brittle limestone. The penetration effect of the triangular-shaped charge cover angle on the metal jet, the expansion law of the main explosion crack, and the influence of the limestone directional damage effect are explored. The results show that high-energy metal jet is formed when the initial velocity of the shaped charge cover is lower than the sound velocity of the shaped charge cover material. The values of B1 and B2 of the original rock are 22.1 and 248.76, respectively, demonstrating the mechanical properties of high strength, high brittleness, and easy fracture. The evaluation index is brittle limestone, and the directional precracking effect of shaped charge blasting technology is remarkable. When the angle of the shaped charge cover is 90°, a penetrating crack is almost consistent with the direction of the precrack generated after the explosion. Moreover, the width of the slit is approximately 2 cm. The borehole imager scans show that the rock wall in the hole is smooth and stable, the test results are consistent with the simulation results, and the angle of the shaped charge cover is 90°. The results have certain guiding significance for rock blasting technology, surrounding rock control technology, and similar directional fracturing engineering in the karst area of Guizhou province.

Intelligent recognition and identification of fracture types and parameters for borehole images based on developed convolutional neural networks and post-processing

Borehole imaging is one of the main methods for fracture observation in the rock formations, but there is still a lack of identification systems for deriving fracture parameters from borehole images. Additionally, previous research were limited to sinusoidal fractures. In this study, an intelligent system is developed for multiple types of qualitative fracture identification in a quick and robust manner using convolution neural networks and post-processing. Initially, borehole imaging was carried out in six coal mines to develop a borehole image database that includes a wide variety of rock types and fractures. Afterward, the acquired borehole images of fractures were categorized into three types, such as sinusoidal fractures, vertical fractures and broken areas. In this connection, dual convolutional neural networks were developed to recognize fracture type pixels. Meanwhile, the calculation models associated with corresponding fracture parameters were established to quantitatively describe the fracture characteristics. Eventually, the post-processing programs were developed to identify the geometric parameters for each fracture type. The results indicate that the developed dual convolutional neural networks has the capability to detect fracture pixels with a recognition accuracy of 77.1% for each sinusoidal and vertical fracture pixels, and recognication accuracy of 72.9% for broken area pixels. The post-processing program was developed based on Hough transform and a thinning algorithm, that enables it to the the average recognition rate of 88.71% with an average false alarm rate of 16.67% for all three types of fractures.

Pre-salt carbonate cyclicity and depositional environment: NMR petrophysics and Markov cyclicity of lacustrine acoustic facies (Santos Basin, Brazil)

The Pre-salt strata are idealized as a lake-dominated breakup depositional sequence recorded between the South American and African continental margins to which there is no present-day analog. Most of the complexities of the Pre-salt reservoir rely on addressing carbonate cyclicities at different scales using limited cored intervals where well-log and seismic correlation is still unclear. In this case, the application of borehole image logs (BHI) and nuclear magnetic resonance (NMR) techniques allows not only the scale correlation and extensive data acquisition but also to establish a more robust relationship between acoustic facies and their petrophysical significance. For that, this work combines BHI and NMR data to propose a feasible scheme of depositional acoustic facies for the Barra Velha Formation in the Santos Basin. To verify the statistical significance of the acoustic facies’ vertical organization, this work applied the Markov chain analysis along a c. 500 m stratigraphic interval, deriving four carbonate cycles associated with shallowing and reworking lacustrine cyclicities. Abrupt changes in cyclicity patterns were adopted as stratigraphic markers to subdivide the succession into lowermost, intermediate, and uppermost intervals that record the depositional history of deep, shallow, and emergent lake environments, respectively. By comparing the thickness variation of the Markovian cycles (i.e., accommodation space) with the seismic onlap curve variation (i.e., lake level) throughout the Pre-salt interval, a larger-scale superimposed cycle was unraveled, suggesting that accommodation space of the studied Pre-salt paleolake was likely controlled by fluctuations in the lake level. Finally, this work aimed to explore the applicability of diagnostic criteria for the description and interpretation of depositional acoustic facies, their petrophysical significance, and cyclicity patterns in the Barra Velha Formation.

How to estimate the 3D stress state for a deep geological repository

Abstract. When stresses yield a critical value, rock breaks or pre-existing faults are reactivated, generating pathways for fluid migration. Thus, the contemporary undisturbed stress state is a key parameter for assessing the stability of deep geological repositories and for quantifying whether stress changes induced by sub-surface constructions and storage of heat-generating waste lead to a critical state. The prediction of the contemporary 3D stress state is achieved with geomechanical–numerical models that are based on the static geological models. These are based on 3D seismic imaging and borehole data and describe the 3D structure and distribution of rock properties. Furthermore, pointwise measurements of the stress state are needed to fit the model to these data. The workshop is divided into three parts. Each part will have a short introduction to the specific topic, followed by dedicated hands-on exercise in small groups and discussions of the exercise outcome and its implications. 1. How do we formally describe the stress field? Here you will learn that the stress field is different from other physical field quantities such as temperature or displacement. The latter can be described with a scalar or a vector at a point. In contrast, the stress state at a point is described with the so-called Cauchy stress tensor that has nine components. We will give a quick tour through this concept, starting from very basic physics, and explain why the tensor is needed. In particular, you will learn in the exercises that stress cannot be measured directly with most methods but that strain is observed, from which stress is inferred.2. How do we actually measure stress? We present a range of methods that determine individual components of the stress state. In the exercise you will analyse borehole image logs to identify borehole breakouts and drilling-induced tensile fractures at the borehole wall. These are used to derive the orientation of the minimum and maximum horizontal stresses. Furthermore, we will present methods for the estimation of stress magnitudes. These are essential data for the calibration of a 3D geomechanical model. We will give a brief overview of different methods and in the exercise on the analysis of mini-hydraulic fracture tests as well as on the sleeve-fracturing and sleeve re-opening methods.3. From a viewpoint to a 3D description. If rock properties in the sub-surface were homogenous and isotropic and were to follow a simple linear behaviour between stress and strain, we could estimate the stress state analytically. However, this is not the case, and we will discuss three questions. a. How many pointwise stress data are needed to efficiently constrain a 3D model?b. How do I know whether a data point taken from less than a cubic metre is a good representation of a large rock volume, i.e. a whole lithological layer?c. How can we quantify the uncertainties of the model stress state, and what is the typical range? You will use a case study in northern Switzerland to explore these questions.

Automatic borehole fracture detection and characterization with tailored Faster R-CNN and simplified Hough transform

Understanding the geological information of fractures from borehole images is essential for conducting a thorough geological analysis in engineering. Recently, the convolutional neural network (CNN) has been employed to extract high-level features of fractures from images. We propose an improved Faster R-CNN (region-based CNN) model for fracture detection, which is suitably equipped with a tailored region proposal network f-RPN for borehole fractures. The anchors generated by f-RPN are specifically designed with a fixed width and varying heights, and only the anchors with the maximum intersection-over-union values are labeled as positive. By taking advantage of the cyclic feature of borehole images, the images are expanded in four orientations to increase the amount and diversity of the model input. The detection results of the model can further be utilized to simplify the Hough transform for characterizing dip angles and dip directions of fractures. The proposed method is validated with borehole images from multiple projects in hydraulic engineering. Experiments reveal that the average detection accuracy is approximately 91.5%, which exhibits an improvement of 11.06% compared to the original Faster R-CNN. Further analysis indicates that both f-RPN and the multi-orientation expansion contribute to improving the prediction accuracy. It is also shown that this method demonstrates robustness against blurred image background and outperforms traditional image processing methods in the presence of noise. The fracture characterization by the simplified Hough transform turns out to be computationally efficient and accurate, with the absolute errors less than 5° compared to the manual identification results.

Characterization of silicification and dissolution zones by integrating borehole image logs and core samples: a case study of a well from the Brazilian pre-salt

Precise knowledge of the spatial distribution patterns of non-matrix porosity zones and the establishment of the geological factors controlling their evolution are crucial for building more accurate carbonate reservoir models and improving hydrocarbon production. The occurrence of intervals affected by significant carbonate dissolution may result in drilling fluid loss and time-consuming drawbacks during well construction. Vug or cave-rich reservoirs may exhibit excess permeability and extremely high initial flow rates. Similar situations have been reported in exploration activities in the Brazilian pre-salt plays, where evidence of dissolution and other burial diagenetic processes, such as severe silicification and dolomitization, are common. In this study, we investigate evidence of major post-depositional changes in the lacustrine carbonate reservoirs of the Barra Velha Formation, which comprises the most prolific hydrocarbon play in Brazil. Using a comprehensive database consisting of both core samples and well-log data from a vertical well in the Santos Basin, we have characterized, at multiple scales, reservoir zones affected by silicification and carbonate dissolution. In addition, we have performed a petrophysical evaluation of the reservoir to understand the impact of such processes on porosity and permeability development. The results suggested an intimate relationship between silicification and dissolution processes, which can be associated with late fluid percolation under a deep burial flow regime. The occurrence of silicified and vuggy beds, associated with specific zones and lithofacies, indicates an important degree of stratigraphic control on fluid percolation and lateral migration. Furthermore, the presence of fractures at discrete stratigraphic levels has preferentially influenced the development of high-permeability zones, including metric-scale fracture-related conduits. This study contributes to the general knowledge of carbonate reservoirs affected by silicification and dissolution while providing support for the recognition of such processes in partially- or non-cored wells.

Computer vision techniques applied to automatic detection of sinusoids in borehole resistivity imaging – A comparison with the MSD method

In this research computer vision techniques are applied to borehole resistivity imaging in order to establish an alternative procedure to the mean square dip (MSD) processing. The MSD is regularly applied to detect sinusoids and dips automatically in borehole imaging and dipmeter logs. The present proposal is based on Gabor’s filters, morphological transformations, Hough’s transform, and clustering techniques. The MSD method and the computer vision proposal were tested in 1012 m of images, showing 7.986% of false positives for the MSD processing and 0.879% for the computer vision approach. This methodology tries to emulate the geologists behavior when they make image interpretation; instead of making correlations between resistivity curves like the MSD does. There are no special computer requirements, and it can be applied directly in the field for quick well-site dip results. This procedure can be easily integrated into log units and most commercial borehole-imaging processing software. The processing workflow was developed in python using standard libraries.

Characteristics and controlling factors of natural fractures in deep lacustrine shale oil reservoirs of the Permian Fengcheng Formation in the Mahu Sag, Junggar Basin, China

Maximum burial depth of the Permian Fengcheng Formation, which contains significant oil resources in the Mahu Sag, exceeds 4500 m constituting a deep reservoir. Fractures are widespread in the deep lacustrine shale, providing important storage space and fluid conduits. Based on cores, borehole image logs, and petrographic analysis, we identified and analyzed the types and characteristics of fractures and conducted X-ray diffraction (XRD) and Cathodoluminescence (CL) tests to investigate the factors influencing fracture development. We found faults and three types of opening-mode fractures: bed-bounded fractures, unbounded fractures and bed-parallel fractures. Mechanical stratigraphy (depositional rock types modified by diagenesis) and proximity to faults, are main controls of opening-mode fracture occurrence and attributes. Specifically, Dolomitic mudstone with a high carbonate content shows the highest fracture density of 5.24 m-1. Bed-bounded fractures are mainly developed within brittle layers, with fracture density lower in thicker beds. On the other hand, unbounded (tall) fractures primarily occur near reverse faults (0–1500 m), with orientations parallel to extension directions implied by the kinematics of nearby faults. Additionally, the effectiveness of early-formed fractures as fluid conduits is likely modified (reduced) by cementation and enhanced by dissolution. Fractures have a positive influence on oil production, corresponding to high fracture density and aperture in the vertical direction.

Modelling of flow through naturally fractured geothermal reservoirs, Taupō Volcanic Zone, New Zealand

BackgroundNumerous fractures are observed in fractured geothermal reservoirs on borehole images in the Taupō Volcanic Zone (TVZ), Aotearoa New Zealand. These fractures are necessary to explain the sustained reservoir permeabilities despite the low matrix porosity. However, conventional continuum models do not adequately represent fluid flow through these fractured rocks.MethodsWe present new Discrete Fracture Network (DFN) codes that model fractures and associated fluid flow in 2-D at reservoir scales to represent typical rock types found in TVZ reservoirs. Input parameters are derived from interpretations of borehole images at the Rotokawa and Wairakei geothermal fields where fractures have high dip magnitudes (> 60–70°). This paper focuses on the effect of fracture density along virtual boreholes (P10), that is in average 0.6 m−1 in sheet-like andesites; 0.8 m−1 in ignimbrites and 1.7 m−1 in rhyolite lavas.ResultsThe number of fractures in the models scale linearly with the input P10 in virtual boreholes. The percolation threshold, where the backbone of fractures is connected across the entire model domain, is reached for P10 > 0.24 m−1. Above this threshold, mean flow measured along the mean fracture direction scales linearly with P10. For P10 > 0.4 m−1 the permeability anisotropy lies in the interval 13 ± 3, with the scatter decreasing as P10 increases. The pressure distributions in individual DFN realisations are highly variable, but averages of 50 realisations converge towards those given by equivalent continuum models. Probability density functions resulting from DFN realisations can therefore be used to constrain continuum models. Tracing of fluid particles through the DFN shows that particles can take numerous pathways to define a swath of paths. The travel time of particles over 1 km follows a distribution similar to real tracer tests, with arrivals peaking at 1–2 days and a long tail stretching to over 200 days.ConclusionsThe new codes, calibrated to real measurements of fracture geometries in borehole images of the TVZ, reproduce patterns of flows in fractured geothermal systems. Mean flows and permeability anisotropies derived from the DFNs can be used to improve modelling of flows through fractured geothermal reservoirs using continuum models at a limited computational cost.

Multidisciplinary Integrated Approach Unlocks Fracture-Characterization Ambiguity

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 213771, “Unlocking Fracture-Characterization Ambiguity: A Multidisciplinary Integrated Approach,” by Ali Abughneej, Mohamed Al-Naqeeb, and Mohammed Al-Ostath, SPE, Kuwait Oil Company, et al. The paper has not been peer reviewed. _ Fracture systems play a significant role in production in the case of tight, low-porosity complex reservoirs. An exploration well in North Kuwait that targeted the Middle Marrat formation encountered uncertainty regarding reservoir compartments in an underexplored field, with minimal offset wells to properly evaluate its potential. A multidomain approach is proposed leveraging different types of expertise to tackle the petrophysical and geomechanical aspects of the fracture system governing the carbonate layer and assess its producibility and qualification for stimulation through hydraulic fracturing. Introduction A comprehensive study was performed on Well A targeting the Marrat formation, a tight, low-permeability carbonate Jurassic reservoir. During the last two decades, the operator has drilled many vertical and deviated wells through this formation. Hydrocarbon production from the closely spaced wells shows a major variation in flow rates, which has been attributed to the presence of uncharacterized fracture clusters as well as the limited understanding of reservoir compartmentalization. To address the challenges of production discrepancy, an innovative multidomain approach was proposed as an integrated solution in an attempt to understand the fracture systems governing the reservoir setting and its compartments and further assess their connectivity and extent to form a perspective on their possible contribution or hindrance to flow. An end-to-end comprehensive work flow was created combining the results of advanced formation evaluation, high-resolution borehole imaging, and state-of-the-art sonic imaging [the 3D far-field sonic (3DFFS) approach], followed by a fracture-stability analysis for the purposes of completion optimization and potential future hydraulic fracture design. Geological Setting Middle Marrat is targeted as the hydrocarbon-bearing zone, consisting of dolomitized oolitic grainstone to packstone facies, reflecting the high-energy inner-midramp shoal depositional environment.