Unlocking Depleted and Low-Modulus Telisa Sandstone Reservoir with Pillar Fracturing Technique: Well Performance Improvement Comparison with Conventional Fracturing

Forecasting the Effectiveness of Well Performance Improvement Techniques

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1079/7/072037 ◽

2021 ◽

Vol 1079 (7) ◽

pp. 072037

Author(s):

K F Gabdrakhmanova ◽

G R Izmailova ◽

L Z Samigullina

Keyword(s):

Performance Improvement ◽

Well Performance

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From Wellbore Breakout to Sand Production Prediction: An Integrated Sand Control Completion Design Methodology and Case Study

10.2118/205935-ms ◽

2021 ◽

Author(s):

Caleb DeValve ◽

Gilbert Kao ◽

Stephen Morgan ◽

Shawn Wu

Keyword(s):

Particle Size ◽

Sand Particle ◽

Well Performance ◽

Sand Production ◽

Natural Sand ◽

Reservoir Development ◽

Sand Control ◽

Production Wells ◽

Sandstone Reservoir

Abstract Controlling downhole sand production is a well-known and often-studied issue within the oil and gas industry. The methods employed for sand management, and their ultimate cost, is greatly impacted by the amount of sand produced by the well. This paper presents an innovative, physics-based approach to predict sand production for various reservoir and completion types, explored through a case study of recent production wells in a sandstone reservoir development. Sand control may be executed through a variety of methods, for example at the reservoir-completion interface using a sand control completion, at topside facilities through sand monitoring / de-sanding equipment, or by using well operational limits to avoid downhole sand failure. Although different strategies exist for effective sand management, some capability to estimate sand production is needed to design a holistic sand management strategy. This paper presents a physics-based approach to predicting sand production on a well-by-well basis to inform the overall sand management design. The workflow integrates (1) geomechanical estimate of wellbore breakout and volume of failed sand downhole, (2) log-based prediction of the sand particle size variation along the well path, (3) modeling of sand filtration based on experimental and analytical methods for specific completion options (e.g. Open Hole Gravel Pack [OHGP] or Stand-Alone Screen [SAS]), and (4) a natural sand pack permeability prediction for SAS completions and associated well performance analysis. This paper describes the methods used in this work in more detail as well as the application to five wells in a recent sandstone reservoir development. The workflow can be described as follows: First, log-based predictions for geomechanical properties and sand Particle Size Distributions (PSDs) were generated for specific wellpaths, and the volume of failed reservoir sand and PSD characteristics were predicted along the entire wellbore length. Next, this analysis was combined with a novel filtration model to determine sand retention and production, specific to various completion types. Additionally, for a SAS completion, the PSD and volume of retained sand in the annulus was computed as the wellbore experience borehole breakout, combined with an analytical model to calculate the natural sand pack permeability and well performance. This workflow was initially applied to study five development well producers, and the results influenced a mixed design of OHGP and SAS completions for individual wells. Sand production was measured during recent well startup to validate the workflow, with excellent agreement observed between measured field data and the physics-based predictions. This innovative, physics-based approach and the associated case study demonstrate a significant advancement in the area of sand production prediction from hydrocarbon production wells. The current workflow is able to deliver improved sand prediction capabilities over rules of thumb or analog field performance, which can be used to better inform overall sand management strategies and associated business value.

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