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Modern computers have allowed the development of increasingly sophisticated models of resistivity logging tool response to actual logging geometries. Significant progress has also been made recently in the inversion of logging data to obtain actual formation parameters. Until we achieve the goal of completely automatic real-time 3-D inversion of logs, such sophisticated forward models can be very helpful in analyzing unsolved interpretation problems. Several of these problems will be examined in detail in this paper. A particularly difficult situation to analyze occurs when features of interest are much smaller than the resolution of the tool. This is the case for induction response in highly laminated reservoirs containing thin layers of oil bearing sand and non-reservoir shale. In these reservoirs, we would like to determine the resistivity of each constituent of the laminated zone and the relative amounts of sand and shale present. Modeling ILD response to sequences of several dozen sand-shale laminations ranging from 1" to 1'' in thickness, we verify that the tool response is predictable when expressed in terms of conductivity instead of resistivity; it is simply a linear average of the volume sand times the sand conductivity plus the volume shale times the shale conductivity. Using core data or a micro-resistivity log such as a micro-electrical scanner image to determine the relative amounts of sand and shale present in laminated zones, this relationship can be applied to solve for the unknown conductivity of the sand laminations and thus estimate water saturation and produceability. In conjunction with modeling laminations, we also analyze how severe dip must be to significantly effect ILD response in the limiting case of three thin beds. Another area where modeling is helping to solve an induction interpretation problem is in the analysis of erratic oscillations that occur on some dual induction North Sea logs in high resistivity formations logged using oil based muds. In this case, a finite element model is used to simulate several different sets of conditions that log analysts have suggested as possible causes of these oscillations. Some of these suggestions are, oil base mud filled cracks, laminations, or layers containing magnetic materials. By elimination, it is shown that the only way these erratic logs can be reproduced is by modeling a conductive anomaly near the borehole wall. The origin of conductive anomaly is still open to discussion. Some gestions have been, breakdown of the mud emulsion high pressures and temperatures, or the build-up conductive mudcake from the saline water in the emulsion. More information is needed about borehole conditions at the time these logs were run before definitive conclusion can be reached.
Periodic changes in depositional environments due to Milankovitch astronomical-climate cycles can cause cyclic patterns in sediment properties as recorded by logging data. Spectral analysis of logging data can identify these regular cycles and be related to the known Milankovitch periodicities, thereby providing actual sedimentation rates. Where accumulation rates are variable, application of a closely spaced series of sliding windows through the logging signal can detect variations and discontinuities in rates of sedimentation.
The temperature log as a part of a production logging package has been used in the industry for many years. Recent developments in downhole fiber optic sensing technology introduced a more continuous measurement of temperature both temporally and spatially for flow diagnosis. One of the powerful applications of temperature measurements is to diagnose multistage fracture treatments. Because the fiber optic temperature measurements can be available during fracturing, during shut-in, and during production, the integrated interpretation provides information of fracture/flow distribution. This information helps to understand what happened during fracture treatments, to identify problems in treatment design and execution, and to improve the efficiency of multistage fracture stimulation.
The key component of fracturing diagnosis by temperature measurements is the interpretation models. In this paper, we present the models developed for fracture diagnosis. The mathematical models are built on mass, momentum and energy conservation of each component (reservoir, fracture, well completion and wellbore) in the system, and the components are linked through the boundary conditions. All models can be solved numerically, but for computational efficiency, analytical/semianalytical solutions are preferred when available. To correctly simulate heat transfer during fracture propagation, a fracture geometry model with appropriate leak off description is integrated into the model buildup. For flow problem in a fractured well, analytical model, streamline approach and reservoir simulation can all be the solution methods. The paper compares the advantages of each approach.
Field cases from the Eagle Ford and the Marcellus shale formations are presented in the paper to illustrate how the models can be used to generate the fracture/flow distribution. The results show that temperature measurement is a comprehensive tool for fracture diagnosis.
Donald, J. Adam (Schlumberger) | Bennett, Nicholas (Schlumberger) | Schlicht, Peter (Schlumberger) | Van Kleef, Franciscus (ADNOC Offshore) | Verma, Ravi (ADNOC Offshore) | Suliman, Israa (Schlumberger) | Hirabayashi, Nobuyasu (Schlumberger) | Al-Kharusi, Saif (Schlumberger) | Karpekin, Yevgeniy (Schlumberger)
ABSTRACT High-resolution wellbore measurements such as microresistivity images are routinely used to define structural information such as formation dip and azimuth to compare with low-resolution seismic migration. The scale differences between microresistivity images and seismic images range from millimeters to hundreds of meters, which is then compared with vertical seismic profile (VSP) data at tens of meters of scale and sonic velocities at less than 0.5 m scale. Sonic imaging techniques from both monopole and dipole sources can be further used to extend the volume of investigation around the wellbore and define true dip and azimuth of the formation extending 25–30 m into the reservoir. When using the dipole source for sonic imaging and recording the single-receiver sensor data, we observe polarized shear reflections that present not just the linear and sinusoidal moveouts evident as a function of source-receiver offset and nominal receiver azimuth, but also a significant polarity signature that is a function of the reflected wave’s particle motion direction. A variation of 3D slowness time coherence (STC) is presented that correctly processes these polarized shear reflections to determine the dip and azimuth of the reflector. We then demonstrate how this new 3D STC processing is integrated into an automated processing that locates and characterizes the reflected arrivals in the filtered waveform measurements and then maps the corresponding reflectors in 3D along the well track. Of note is how the automated processing with the new 3D STC variation resolves the 180° ambiguity of the reflected dipole signal noted by previous authors. This is particularly important when imaging or mapping formation structure in a highly deviated wellbore, because the single-sensor data can image both above and below the wellbore, compared with conventional modal decomposed dipole waveforms, for which distinguishing top from bottom is ambiguous. A case study is presented from offshore Abu Dhabi, in which an interbedded carbonate reservoir is examined with various acoustics measurements and microresistivity images. A detailed structural analysis is conducted using a walkabove VSP whereby the migrated image below the wellbore is used to compare with the sonic imaging results from azimuthal monopole and dipole sources. Migration images from the dipole shear clearly show subseismic-scale layers in comparison with the VSP migration. Structural dip and azimuth of these subseismic features provide detail 30 m into the reservoir.
Abstract In the modern oilfield, borehole images can be considered as the minimally representative element of any well-planned geological model/interpretation. In the same borehole it is common to acquire multiple images using different physics and/or resolutions. The challenge for any petro-technical expert is to extract detailed information from several images simultaneously without losing the petrophysical information of the formation. This work shows an innovative approach to combine several borehole images into one new multi-dimensional fused and high-resolution image that allows, at a glance, a petrophysical and geological qualitative interpretation while maintaining quantitative measurement properties. The new image is created by applying color mathematics and advanced image fusion techniques: At the first stage low resolution LWD nuclear images are merged into one multichannel or multiphysics image that integrates all petrophysical measurement’s information of each single input image. A specific transfer function was developed, it normalizes the input measurements into color intensity that, combined into an RGB (red-green-blue) color space, is visualized as a full-color image. The strong and bilateral connection between measurements and colors enables processing that can be used to produce ad-hoc secondary images. In a second stage the multiphysics image resolution is increased by applying a specific type of image fusion: Pansharpening. The goal is to inject details and texture present in a high-resolution image into the low resolution multiphysics image without compromising the petrophysical measurements. The pansharpening algorithm was especially developed for the borehole images application and compared with other established sharpening methods. The resulting high-resolution multiphysics image integrates all input measurements in the form of RGB colors and the texture from the high-resolution image. The image fusion workflow has been tested using LWD GR, density, photo-electric factor images and a high-resolution resistivity image. Image fusion is an innovative method that extends beyond physical constraints of single sensors: the result is a unique image dataset that contains simultaneously geological and petrophysical information at the highest resolution. This work will also give examples of applications of the new fused image.