Image artefacts, that is, non-geological features present on acoustic or micro-resistivity borehole image logs are a fact of life. In poor quality image logs, they can constitute the bulk of the data-set although fortunately, such features generally constitute the minority of a data-set. The recognition of artefact features must form part of the log quality control process and should also form part of the interpretation process. By applying sound log quality control principles, these artefacts can be identified systematically and the remaining image data will be geologically related. This paper provides an up-to-date summary of borehole image artefacts, their cause and recognition. It also, for the first time, considers artefacts arising from acoustic (ultrasonic) as well as micro-resistivity images. Four main artefact image categories related to data acquisition, borehole wall condition, post processing of data and measurement physics form the basis for the systematic identification procedure. These are discussed and developed herein.
Core-log comparisons are often not considered routinely enough within the exploration environment. This may be for a number of reasons, such as problems with depth-matching the core and log datasets, the environment of acquisition of both datasets, the lack of understanding of log and core acquisition or a lack of confidence in laboratory or log measurements. These problems are discussed as a preliminary step to the development of a strategy aimed at improving core-log integration.Using recent technological advances in the side-by-side presentation of core and high resolution image data from logging tools, a strategy is presented with the aim of making core-log integration more rigid and routine. Features in both core and images are correlated interactively--thus ensuring the best possible integration. This is a two stage process involving core-to-image matching, and then image-to-log matching. This strategy has the potential to make core-log integration more accurate and as a result enable the interpreter to realize the most from sub-surface data.Borehole logging provides quasi-continuous (typically every 150mm), in situ measurements
Ultrasonic borehole image tools are generally considered to be of limited value as an interpretative sedimentological tool because thick packages of a single lithology have similar acoustic properties resulting in resolution of very little diagnostic detail. In addition, build-up of mudcake in porous sandstones typically masks geological information by impeding the acoustic signal. In contrast, in heterolithic sediments, differences in acoustic impedance between intercalated lithologies enable clear distinction of sandstones and mudrocks from ultrasonic amplitude images. Whilst resolution of internal detail is still limited, valuable diagnostic data may be obtained for the sandstones by careful examination of the geometries and orientations of their lower and upper contacts with enclosing mudrocks. This is the case in the Lower Kimmeridge Clay Formation reservoir in the Magnus Field, UKCS, using the Schlumberger Ultrasonic Borehole Imager tool (UBI). Here, the bulk of the reserves are held in relatively thin, depositionally flat-lying, high-density turbidite sandbodies which are donors to variably inclined and complexly bifurcating sandstone injections. Recognition of sandstone injections and an understanding of their orientations is crucial to future development of this reservoir because they may be the principal means of communication between sandbodies and also have pay potential. Whilst this is not possible using conventional openhole logs it is easily achieved using UBI amplitude images.
Summary Accuracy of measurement while drilling/logging while drilling (MWD/LWD) depth measurements can be improved by considering the dynamic variation in drillstring length caused by pipe loading under changing drilling conditions. This paper details a new method that uses surface torque, hookload, and temperature measurements to determine force distribution in a drillstring and to compute apparent drillstring length. When available, torque, weight on bit (WOB), and temperature measured downhole are used to increase accuracy and robustness of the method. Although logging depth is referred to as a measurement, in reality only the drilling block position is measured. Depth is inferred from it using drillstring length. In recent publications, physical phenomena affecting this were analyzed and quantified. Elastic pipe stretch and thermal expansion were found to be most significant. Techniques to compensate for these effects on the basis of empirical formulae have been proposed (Brooks et al. 2005), but they provide an averaged correction that has insufficient accuracy for many drilling and formation evaluation applications. This paper presents experiments covering various wellbore profiles, temperature profiles, and drilling modes, which show that the depth fluctuation may be as much as 2.7 meters with a 7,000-meter (m) long drill string even when only the current rig operation mode changes. Among other factors considered in the paper, apparent depth fluctuation is the most significant contributor to commonly observed MWD/LWD log discrepancies when bed boundaries or other features are not logged at the same depth with each sensor. These errors lead to inaccurate petrophysical calculations, distortion of borehole images, and lost time caused by depth matching. Case studies illustrate the positive effect of dynamic depth correction on formation evaluation log quality. The accuracy of a depth measurement is normally estimated in terms of its bias and uncertainty. A significant portion of the depth bias is caused by elastic stretch and thermal expansion (for example in a 7,000-m long vertical drillstring they can be 9 m and 6 m, respectively). The proposed method removes this bias and allows improved depth uncertainty. Measured depth uncertainty (1 sigma) in the Industry Steering Committee on Wellbore Surveying Accuracy (ISCWSA) MWD model caused by drill string stretch is 2.2 X 10-7 m-1, multiplied by measured depth (MD) and by true vertical depth (TVD). Uncertainty in measured depth cannot be completely eliminated even by applying corresponding corrections because of the modeling and input data inaccuracies. Nevertherless, it is estimated that the proposed method significantly reduces this uncertainty (e.g., 50% and more, depending on the wellbore, available data, etc.). Improved depth accuracy, in turn, reduces the uncertainty in computation of reservoir characterization parameters, such as net-to-gross and structural dip, especially when data from multiple wells are evaluated together. Introduction Depth is one of the most important formation evaluation measurements, but one of the most difficult to define accurately. Previous publications (Wilson et al. 2004; Brooks et al. 2005; Pederson and Constable 2006) detail this problem as occurring to various degrees for both wireline- and drillpipe-based systems. With longer and deeper wells in deeper provinces around the world, and the use of drill pipe conveyance (MWD/LWD), this problem becomes more acute. Awareness of the financial as well as technical implications for inaccurate depth is increasing. Depth accuracy is also vital for accurate calculation of structural dip from borehole images, picking perforation points, and correlation of geological units. MD is used directly in the calculation of TVD—the primary depth used for reservoir delineation. Wilson et al. (2004) explore one such case in which a 2-m TVD discrepancy in oil water contact (OWC) has a widespread implication for the field development plan, pressure support, and compartmentalization with a significant cost attached. Errors in depth are difficult to detect using a single scalar measurement, however, comparison of multiple curves, which have similar character (Fig. 1) and array measurements, often readily exhibit these artifacts. It is common practice to use a cross-correlation and depth "rubber-banding" technique to bring MWD/LWD measurements from different sources (even within the same bottomhole assembly [BHA]) together, using measurements from the sensor closest to the bit as a reference. This practice addresses the symptom but not the cause, with no reliable reference or rationale (e.g., the sensor closer to bit generally is not more accurate). Misalignment of curves serves as a good indicator of the formation evaluation (FE) measurements depth placement uncertainty. It should rather be used for validation of methods used to convert LWD/MWD data to depth logs. This paper discusses the source of the marked relative variations between FE measurements and concentrates on improvement in the accuracy of drillstring-derived depth for MWD/LWD, which leads to smaller uncertainties around the calculation of final TVD. The integrity of the depth measurement can be described by a variety of terminologies, generally depending on the application of depth under discussion. Wellbore placement, tying in formation evaluation data with seismic sections, and crosswell correlation all rely on accurate absolute depth (both measured and calculated TVD). Depth accuracy is the degree of conformity of the measured value to the true value.
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