Critical drawdown pressure for sand onset and its accuracy with change in water cut is a continuous area of study. The numerous parameters like grain cementation, viscosity of fluids, actual physics of sand production with fluids leads to a lot of uncertainty. In practical terms, it has been observed that these mechanisms lead to reduction in Uniaxial Compressive Strength of rocks. The objective of this paper is to present a novel method that not only helps on understanding the effect of water production on sand failure but to further predict the volumetric expected sand production up until a certain tolerable error.
A sand prone field within Malaysian region was identified and core tests were done to evaluate UCS and other rock strength parameters at different saturation of water to simulate the effect of water on rock strength. CDP evaluations were done and the values were calibrated with actual field data to have an accurate understanding of CDP values at different water cuts. Lastly, with the findings from field production data, limit was pushed further to develop a novel method to predict the volumetric sand production.
The proposed novel method has helped not only in understanding the effect of water production on sand failure but also on the amount of sand to be produced under different drawdown pressures with a reasonable accuracy. These results proved very useful in implementing Company's Holistic Sand Management strategy. The integration of this method with water cut predictions from reservoir simulation models helped the team to quantify the continue increasing sand production due to water cut increase. Company is replicating similar workflow in other sand prone fields for an effective sand management.
The approach is very novel as the theoretical modelling work has been effectively calibrated using real field data. This method has provided a high degree of confidence in estimating the amount of sand to be produced under different production conditions.
Authors consider this as a breakthrough in field of holistic sand management and very useful workflow for all other operators to emulate.
Tugimin, M Azri Aizat (PETRONAS Carigali Sdn Bhd) | Kamat, Dahlila (PETRONAS Carigali Sdn Bhd) | Baghdadi, Faical (PETRONAS Carigali Sdn Bhd) | Gupta, Anish (PETRONAS Carigali Sdn Bhd) | Mohammad Azili, Ammar (Schlumberger) | Mohamed Hanafi, Muhammad Mukrim (Schlumberger) | Meza, David (Schlumberger)
Sand Monitoring workflow was introduced in R field to manage and minimize the risk that sand production poses to the production facility by monitoring the sand production and its resulting erosion rate, and raise alarm immediately when these conditions violates the allowable threshold. The workflow serves as an enabler to the sand management process that are put in place at the field. By leveraging the automation from IO and complement it with additional processes, we came up with a holistic approach that is used to minimize the risk to the production facility. The defined Sand Management methodology starts with the automated workflow processing. The workflow utilizes data from field sensors and processes them to conduct risk assessments, and some mathematical calculation that are based on proven correlations. Based on these processes, the workflow will generate output of sand production risk assessment, calculated erosion rate, estimated remaining pipe thickness as a result from the erosion rate and critical drawdown monitoring.
To complement the output from the workflow, additional processes that utilizes the outputs are introduced as part of the sand management process. Some of these additional processes are: Correlation calibration by comparing the estimated pipe thickness from the workflow against computerized radiography or unit thickness manual measurement. Conduct Sand Depositional modelling at the high-risk location identified from the workflow to optimize sand handling capacity and monitoring. Extend the monitoring by utilizing network modelling software to assess the erosional risk from interlink of pipelines between jackets. Choke health monitoring and estimation based on choke CV and modelling.
Correlation calibration by comparing the estimated pipe thickness from the workflow against computerized radiography or unit thickness manual measurement.
Conduct Sand Depositional modelling at the high-risk location identified from the workflow to optimize sand handling capacity and monitoring.
Extend the monitoring by utilizing network modelling software to assess the erosional risk from interlink of pipelines between jackets.
Choke health monitoring and estimation based on choke CV and modelling.
The sand monitoring workflow has increased personnel efficiency by automating repetitive and tedious work and give out the result in an easily interpreted manner. The automated alarm has been proven to be useful in proactively engaging operations to tackle the problematic matter. Production interruption related to sand production has been effectively reduced by 50% after the implementation of the new Sand Management methodology.
The introduction of the workflow into the new methodology uses marginal cost, but maximizes the return on existing asset through the realization of their production potential, as well as proving on how multidisciplinary integration and collaboration between operator and the service company can be successful in a mature field despite the risk associated.