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Sand Volume Quantification with Applications in Sand Screen Selection
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Abstract
Sand production prediction is essential for completion design and production management. A complete SPP includes the critical sanding pressure condition (timing), the sanding interval and the sanding severity (volume). Sand volume quantification is an important input for surface facility design, erosion modelling, sand screen testing and the overall sand management decision. In this paper we introduce a new methodology combining analytical and numerical sanding prediction to estimate both the onset of rock failure and volume of failed rock. For sand quantification in open hole completion, we use a combination analytical Poro-Elastic and Poro-Elasto-Plastic rock failure models. For cased and perforated completions, we use a combination Analytical Poro-Elastic and a previously published sand quantification model. The results are cross-checked with numerical simulations and field data (when available) for calibration and validation. The application of this new sand volume quantification methodology in sand control selection is shown in a field study
The conventional selection procedure for standalone sand screens uses the "auto-pack" concept by assuming a rapid collapse of formation on the screen and filling of the annulus by the failed material via natural packing and bridging, thus protecting the screen from erosion and plugging. Such conditions may not happen rapidly enough, hence the selection of standalone screens without adequate qualification could pose a completion risk. The possibility and timing of the "auto-pack" depend on the geomechanical characteristics of the formation and the pressure conditions during production. Advanced geomechanical assessments of formation failure and sand quantification are used to determine the likelihood of formation collapse and the timing of "auto-pack". Combing these analyses with formation grain size data (PSD), sand retention tests (SRT) and erosion modelling offers a more robust qualification process for a variety of screen types.
In the case study, a well-life sanding assessment indicated considerable sanding risks. Analytical sand volume estimation was used in conjunction with PSD to upscale the SRT results to well life conditions. The SRT suggested wire wrap and premium standalone sand screens were needed, where wire warp screen is satisfactory only after auto-packing whilst the premium screen works fine from the start. With minor sanding expected from the onset of production and increasing with depletion, the sand volume quantification showed the time span for a complete auto-pack in a standalone screen application could range from ∼2 years for a vertical cased hole to ∼7 years for a deviated open hole. Hence an erosion- and plugging-resistant sand screen should perform better. Finally, premium sand screens were qualified based on sand retention testing results with further support from the geomechanical estimation of "time to auto-pack" and screen plugging concerns.
This integration improves sand screen selection criteria, increases screen longevity and well productivity utilizing geomechanical and well-life reservoir performance insights.
Title: Sand Volume Quantification with Applications in Sand Screen Selection
Description:
Abstract
Sand production prediction is essential for completion design and production management.
A complete SPP includes the critical sanding pressure condition (timing), the sanding interval and the sanding severity (volume).
Sand volume quantification is an important input for surface facility design, erosion modelling, sand screen testing and the overall sand management decision.
In this paper we introduce a new methodology combining analytical and numerical sanding prediction to estimate both the onset of rock failure and volume of failed rock.
For sand quantification in open hole completion, we use a combination analytical Poro-Elastic and Poro-Elasto-Plastic rock failure models.
For cased and perforated completions, we use a combination Analytical Poro-Elastic and a previously published sand quantification model.
The results are cross-checked with numerical simulations and field data (when available) for calibration and validation.
The application of this new sand volume quantification methodology in sand control selection is shown in a field study
The conventional selection procedure for standalone sand screens uses the "auto-pack" concept by assuming a rapid collapse of formation on the screen and filling of the annulus by the failed material via natural packing and bridging, thus protecting the screen from erosion and plugging.
Such conditions may not happen rapidly enough, hence the selection of standalone screens without adequate qualification could pose a completion risk.
The possibility and timing of the "auto-pack" depend on the geomechanical characteristics of the formation and the pressure conditions during production.
Advanced geomechanical assessments of formation failure and sand quantification are used to determine the likelihood of formation collapse and the timing of "auto-pack".
Combing these analyses with formation grain size data (PSD), sand retention tests (SRT) and erosion modelling offers a more robust qualification process for a variety of screen types.
In the case study, a well-life sanding assessment indicated considerable sanding risks.
Analytical sand volume estimation was used in conjunction with PSD to upscale the SRT results to well life conditions.
The SRT suggested wire wrap and premium standalone sand screens were needed, where wire warp screen is satisfactory only after auto-packing whilst the premium screen works fine from the start.
With minor sanding expected from the onset of production and increasing with depletion, the sand volume quantification showed the time span for a complete auto-pack in a standalone screen application could range from ∼2 years for a vertical cased hole to ∼7 years for a deviated open hole.
Hence an erosion- and plugging-resistant sand screen should perform better.
Finally, premium sand screens were qualified based on sand retention testing results with further support from the geomechanical estimation of "time to auto-pack" and screen plugging concerns.
This integration improves sand screen selection criteria, increases screen longevity and well productivity utilizing geomechanical and well-life reservoir performance insights.
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