Practical Approach To Achieve Accuracy In Sanding Prediction

Abstract

This paper was also presented as SPE 100948 at the 2006 SPE International Oil & Gas Conference and Exhibition in China held in Beijing, 5–7 December 2006. Abstract Sand production is a major concern for many operators. It can impact production, cause erosion in downhole and surface facilities, require additional separation and disposal, and lead to significant economic loss. On the other hand, precautionary but unnecessary sand prevention will mean unwarranted reduction in productivity. Reliable sanding prediction analysis thus provides a basis for designs that achieve appropriate sand management strategies and maximization of economic production, and overestimates or underestimates of sanding risk increase the chances of serious economical loss. This raises the question of how accurate and reliable sanding predictions might be achieved without overcomplicating the analyses and without requiring complex lab and field data that, in most instances, will be unavailable or the acquisition of which will incur unwanted delays and costs. This paper presents the case of a sanding study for the Messla field in Libya; a field that has produced oil for more than 30 years. This field experiences massive sanding from some wells but experiences no problems with other wells. This variation made the Messla field an ideal candidate for a detailed sanding and geomechanics investigation aimed at optimizing completions and production and at dramatically reducing the current sanding without having to enter into a lengthy data acquisition programme or time-consuming modelling. In this study, sanding prediction analyses were conducted using a technique that combines easily measurable lab data, log data, and analytical calculations with empirical methods that are supported by the results from previously run rigorous and advanced numerical code. The result of this integration is a sanding analyses tool that uses input parameters such as rock strength, geostresses, and particle size to:account for plasticity effects that modify the strength behaviour of sands surrounding openhole wells and perforations during drawdown to reduce uncertainty and conservatism such as seen in simple elastic models,account for scale effects associated with different perforation and borehole diameters,provide a significant improvement and predictive capability over simple empirical methods,provide the above accuracies without needing complex or extensive lab programmes to determine advanced rock mechanics properties. The application of this approach to the Messla field and a later comparison of the results to actual field data and observations validated the analyses and methods used. The application and comparison also disclosed that the approach was not only able to provide results that closely matched field experience but was also able to predict correctly, to the year, the onset of sanding in wells. This paper describes the methods employed in this investigation, provides details of the data acquisition and processing required, and demonstrates that accurate sanding predictions can be achieved by focusing effort on certain input data, targeting and reducing specific uncertainties, and by employing pragmatic models that do not rely on over-complicated measurements and analyses. Introduction The giant Messla field is located in the southeast portion of Sirte Basin in Libya, approximately 500 km southeast from Benghazi (see Figure 1). The field, operated by AGOCO, has been producing for over 30 years, and since the mid-1980s some wells have suffered massive sanding while others have not. 1 A geomechanics and sanding study was initiated in 2005 to investigate the reason for this variation, to evaluate the severity of sanding risk in other wells, and to provide the information and interpretations needed to design appropriate completions, maximize economical production and optimize future reservoir management.

Sand production simulation under true-triaxial stress conditions

“…The critical drawdown pressure changes during the life of a reservoir when the other parameters change. (Qiu et al, 2006).…”

Sand Management: What Are We Sure Of?

“…Due to the complexity of the required input data, predictions from complex numerical models (such as FEM) may not be as reliable, or accurate, as simpler analytical approaches that rely on easily accessible input data (Qiu et al, 2006) • Use the sanding prediction model to evaluate the many options available to the sand management team including selective perforation, oriented perforation and the retrofit of sand control. Extended leak-off tests in sand are not easy to obtain but the results are invaluable in constraining reservoir stresses.…”

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.…”