Downscaling Geomechanics Data for Thin Beds Using Petrophysical Techniques

Abstract

Thin-bed sequences, especially those made up of alternating weak and strong sand layers with thickness of less than 1-ft, present a particular challenge in the generation of mechanical earth models (MEMs) for geomechanics design and analyses. Because these beds are thinner than the tool resolution, their heterogeneity and the variations between adjacent layers are often undetected by logging tools normally used to acquire geomechanics data. In other words, these tools cannot resolve the existence of alternating strong and weak sequences; they provide only averaged mechanical properties across these sequences. In one such case, an MEM and sanding study based on wireline sonic data indicated no tendency for sanding across a thick reservoir interval at the drawdowns required for economic oil production. The somewhat flat, log-derived curve of unconfined compressive strength (UCS) indicated that the entire reservoir was above the critical sand-free UCS state; however, laboratory data had revealed a large spread in UCS values, including rock strength values that are indicative of a significant sanding risk. In fact, the field had a history of solids production with depletion. Using the high-resolution images (with vertical resolution of 0.2 in.) provided by a microresistivity imaging tool across the same thin-bed intervals, and using alpha processing and other petrophysical log enhancement to further improve data interpretation, it was possible to generate a high-resolution (around 0.2 in.) porosity log. These downscaling techniques were combined with an empirical UCS-porosity relationship obtained from the available laboratory data. The resulting downscaled UCS log exhibited the wide range of strength values that were known to exist across the thin-bed sequence and were consistent with the history of sand production in the field. The remaining sanding evaluation for the well was completed using this integrated petrophysics and geomechanics approach. When the MEM and sanding analyses were extended to other wells in this field, the results matched well with the actual depletion curves and sanding history data. Introduction The Sarir field in Libya, operated by the Arabian Gulf Oil Company (AGOCO), has been experiencing progressively worse sand production problems in an increasing number of wells since 1984.[1,2] A geomechanics and sanding study initiated in 2004 investigated the probable cause of this problem and provided the information and interpretations needed to select an appropriate sand management solution, assist in future development decisions, allow appropriate completions planning, and optimize future reservoir management. To this end, the results of a data audit identified what geomechanics-related information existed that might be used to characterize previous sanding problems and diagnose their root causes. A laboratory testing programme using cores from the Sarir field obtained measurements of rock mechanics parameters relevant to stress modelling and sanding prediction. [3] Integrating laboratory results with other geomechanics information available from log, field, and drilling measurements provided an initial MEM. This MEM contained most of the information necessary for subsequent geomechanics analyses and sanding evaluations.[4,5] However, one significant finding was that routine UCS determinations from sonic logs in the Sarir field were unable to detect thin weak zones having thicknesses below the tool vertical resolution (i.e., 42 in.) of the sonic wireline tool. Therefore, petrophysical log-enhancement processing6,7 was conducted to obtain high-resolution, downscaled porosity logs using microresistivity image data. These data were then used to derive high-resolution (i.e., downscaled) UCS logs through UCS-porosity correlations. The UCS data from this process, which exhibited the same strength heterogeneities observed in the core data, provided the improved description of rock strength in the MEM that was needed in the subsequent sanding analyses of the thin-bed sequences.

Practical Approach to Achieve Accuracy in Sanding Prediction

“…43 However, all these elastic properties are termed dynamic, and sanding prediction analyses require static moduli. 42 One proprietary correlation was found to give static moduli that, on average, provided a satisfactory match to the static data from the laboratory tests conducted on the Messla cores. Figure 3 shows that the log-derived static Young's modulus (shown as a red log trace in the plot) is consistent with core data from the laboratory test (pink squares).…”

“…It can also: account for plasticity effects that modify the strength behaviour of sands surrounding open-holes and perforations, thereby removing the uncertainty and conservatism otherwise seen in simple elastic models, account for scale (i.e., size) effects that dramatically impact the relative stabilities of different sized perforations and boreholes, provide a significant improvement and predictive capability over simple empirical methods, by providing a computation solution that can be applied across different environments and settings, achieve all of the above and provide increased accuracy without needing a complex or extensive laboratory programme to determine advanced rock mechanics properties. Since this model has already proven successful and accurate in field tests and numerous applications, including previous sanding studies for other AGOCO fields, 42 it was selected for the Messla sanding investigation. The remaining challenge in the project was therefore to minimize uncertainty in the input data that would be used with this model.…”

“…Previous work and studies in neighbouring fields have revealed little or no evidence of any horizontal tectonic stresses being present now. 42 The magnitude of the minimum stress can be measured with extended leakoff tests, data fracs and with the MDT stress tool. However, none of these measurements is available for the Messla field.…”

3D Reservoir Geomechanics Workflow and Its Application to a Tight Gas Reservoir in Western China

“…The '1D' in '1D MEM' stands for that the MEM is built along the wellbore trajectory, which can be either vertical or deviated. The procedure used to build a 1D MEM has been documented elsewhere (Qiu et al 2005, Qiu et al 2006) and is not covered here. This paper presents only the results of the final 1D MEM from the two study wells in the XG field.…”

Underbalanced Drilling of a Horizontal Well in Depleted Reservoir: A Wellbore Stability Perspective

“…Having laboratory test data available to this study allowed more reliable MEMs to be generated. 9,10 A geomechanical laboratory test program and selection of core plugs should be carefully designed to maximize the value of the laboratory tests. Owing to a limitation of the number of core plugs to be tested, representative core plugs should be optimally selected for the laboratory tests.…”