EAGE Borehole Geology Workshop

Borehole image logs are high resolution, orientated data sets which can be used to provide valuable geological information and address a range of subsurface issues. Data quality is of paramount importance when interpreting borehole image logs. The paper will illustrate a simple borehole image QC tracking system, and explore some historical trends in data quality, illustrating the types of data issues that can arise and the impact that they can have upon data integrity. Problem data sets appear to be increasingly common. However, access to processing software and interpretation tools is now very easy, and a beautiful image log may have underlying issues that the casual image log user may not be aware of. For example, our review indicates that common issues encountered are associated with data sets being incomplete, or having problematic image log orientation curves, and these can have a significant impact upon the integrity of the images. Standardisation of QC procedures could have a positive value impact upon the utilization of borehole images, and could also form the basis of quality assurance when image logs are archived.

This study consists of detailed analysis of 17 high-definition microresistivity images from a tight gas reservoir in western China. Most of the images are acquired in OBM with very adverse conditions for the imager tool resulting in limited image quality. Through extensive comparison between core and images and between OBM images and WBM images, we have improved and evaluated the accuracy of natural fracture interpretation from OBM images. In particular, one well is drilled and logged in OBM and then logged again in WBM over the same interval to compare the fracture interpretation results. The comparison shows that even in very harsh logging conditions, most of the fractures interpreted from WBM images can also be identified on OBM images. Interestingly, open fractures on OBM images have a conductive colour likely because of the magnetite used as weighting material in the mud. Thus, zones of effective fractures can be identified. This possibility is validated by mud loss data.

Carbonate Reservoir Textural Analysis: Carbonate formations provide the main reservoirs in the Middle East Region. Many productive carbonate formations have complex dual porosity systems consisting of primary matrix porosity and secondary porosity. The secondary porosity may comprise vugs, molds and fractures. Electrical borehole images provide both high resolution and azimuthal coverage to quantify the heterogeneous nature of the carbonate porosity Clastic Reservoir Textural Analysis: Borehole images in sand/shale formations contain much usable textural information. The Resistivity Spectrum Analysis program creates a semi-automatic product for sand/shale environment that captures this high resolution information. The resistivity image spectrum is calculated over a user-defined interval and an image sorting index is calculated from the percentile distribution of the image spectrum. The resistivity spectrum can be divided into a “well sorted” portion and the fractions that are either more resistive or conductive.

The core provides essential information on grain-size distributions, porosity and permeability variations as well as rock fabric and texture information, which are essential for facies and depositional environment interpretations. Extrapolation and reconciliation of these core lithofacies with open hole derived electrofacies is often problematic, due to the differences in resolutions between the two data types. Core facies are typically “lumped together” into units that can be segregated based upon their log responses. This up-scaling — often based upon log response cutoffs — can lead to differing rock “types” being lumped together because critical textural information related to sedimentary structures is omitted. As a consequence, stratigraphic correlations become based upon recognition of “log shapes,” rather than true reservoir properties, e.g., grain-size trends, bedding attitudes and facies contacts. Integration of core analysis and core descriptions with open hole logs and borehole image-based texture analysis prior to the stratigraphic interpretation can significantly enhance reservoir characterization and stratigraphic correlation. Key core derived information, e.g., grain-size trends, textures or spatial information, can be more readily extrapolated to high resolution borehole images, which in turn provide the essential intermediate link between the physical core and open hole log responses.

The primary objective of this study is to improve the understanding of the fracture system in the reservoir section of the Habban basement field, Yemen. Since basement rocks lack a considerable amount of primary porosity, fractures provide both porosity and permeability for storage and production of hydrocarbons. The results of the study greatly support reserve estimation, well planning and future operation of the Habban field. The interpretation of resistivity and acoustic borehole image data sets from six wells provides invaluable information about the inherent structural elements of the metamorphic basement rock in the Habban field. The structural analysis of the cores added in-depth knowledge about fracture characterization, age relationships of fracture and fault events and provided quantitative information about the shear direction along fault and fracture planes. The fracture classification scheme used in this study is based upon a descriptive methodology to classify fractures based on tool response. For this study three fracture types are distinguished. Type I describes the most possible productive features whereas Type II fractures are classified as possibly productive. Fractures of Type III are classified as low or non-productive. The image fracture classification is calibrated through core observations.

This work presents a case study for a well targeting a mature gas reservoir located in the Rotliegend formation of the North German Basin. The Rotliegend mainly consists of eolian sandstone layers. The reservoir sandstones are known to be at least partially depleted and with increasing exposure time (logging/drilling) prone to borehole stability problems. This, in combination with high differential pressures, causes the risk of borehole collapse and prompts the use of logging while drilling (LWD) technology. This can reduce drilling/logging time and minimize the risks mentioned above. For the first time, a 4 ¾” high-resolution LWD resistivity imaging tool was used in the logging program. The key question was, if the image quality would be sufficient to use the LWD technology in cases where hole-stability precludes the use of conventional wireline logging techniques. A second focus was to determine the depth-of-investigation (DOI) of the LWD tool sensor. Whereas the depth of investigation is well known for the wireline technology (Hansen and Parkinson 1999), this is not the case for LWD applications, where DOI depends on varying mud properties, tool-standoff and formation invasion. Inaccurate determination of the depth of investigation can result in over- or underestimation of the picked dips for bedding, fractures or faults. Earlier studies show that fracture dips and especially the dip angle of lithological units are crucial parameters for reserves estimates. Subtle differences of 2 to 3° in dip angles can result in thickness variations of up to 200 to 300% (Passey et al. 2005). Such inaccuracies are of even bigger importance nowadays, as less profitable oil and gas fields are more frequently exploration targets.

Operators are drilling horizontal wells and performing multi-stage completions to produce large quantities of hydrocarbon from shale reservoirs. However, applying these technologies may not yield consistent, economic production. The causes for poor performance in horizontal wells are: poor placement, completed geometrically, without accounting for changes along the wellbore in rock matrix (reservoir quality, RQ) or stresses (completion quality, CQ), or hydrocarbons and associated pore pressure expulsed through fracturing and/or matrix leak-off. The purpose of this paper is to show the applications of borehole images to optimally place and complete horizontal well in shale plays. Images provide critical information to address RQ and CQ. Images are collected from vertical wells and, together with other tools, aid in the identification of the optimum zone for lateral placement in terms of superior RQ and CQ. The main applications of images on lateral wells are: well placement, mapping structural complexity, capturing the orientation and densities of natural and induced fractures, etc. Changes in these properties will have significant ramifications on the horizontal completion. Borehole images have the potential to provide most of the information needed to steer and place horizontal wells properly, maximizing reservoir contact and permitting an engineered completion that ensures optimized production.

The automation of repetitive tasks in borehole image data analysis has the potential to increase efficiency and consistency, and deliver time savings that can be invested in other aspects of integration and interpretation. This has motivated the development of multiple innovative technologies, three of which are described in this paper: data-driven deterministic reconstruction of missing data to address incomplete coverage from wireline logs (and gaps in LWD images), the calibration and characterization of microresistivity measurements to provide quantitative resistivity values for petrophysical evaluations, and dynamorphic processing for image enhancement, avoiding the artifacts introduced by dynamic normalization. Each development is significant in its own right, but additionally, the inclusion of these technologies in image generation workflows gives automated processes the best opportunity for success. Among these is the robust and rapid identification of planar and sub-planar boundaries - the initial focus of these developments.

Logging-While-Drilling (LWD) images acquired in horizontal wells are characterized by various features that are sensitive to formation structure near the wellbore. In current commercial processing, the different features – commonly referred to as “sinusoids”, “bulls-eyes”, or “reverse bulls-eyes” – are extracted from the images manually. However, manual feature extraction is time consuming and prone to user bias. This is of particular concern in high-angle/horizontal wells, where small errors in structural dip translate to large errors in reservoir volumetrics. Here we present a new automatic method for three-dimensional structural interpretation of sinusoidal and bulls-eye features observed in LWD images. With processing time of a few seconds for hundred feet of data, the method is sufficiently fast for use in real-time analysis, or to provide constraints for physics-based inversion.

A core slab provides geologists a continuous view of the rock in two-dimensions, exactly as one would see in a road-cut or how one looks at any picture. Another very effective source for detailed geological interpretation is the borehole image. Borehole images provide a continuous image of the sub-surface geology as seen in the borehole wall. The images are presented as an unwrapped cylinder of the borehole wall. However, in this view, planes, such as bedding planes, fractures, faults, etc., get displayed as sinusoids rather than as straight lines as seen in core slabs. In this paper, the standard view of presenting borehole images is discussed as a “Sinusoidal view”. If a geologist can be provided with borehole images where planes are seen as straight lines, as in a slabbed core, the geologist is able to extract more information from the image and do superior geological interpretations. This paper discusses an advanced new mode of displaying borehole images – in true two-dimensions in a slabbed-core-like format. The paper also presents cases from different geological settings demonstrating the value of the gain in geological interpretation using the new image visualization format.