Sand production: A smart control framework for risk mitigation

Mahmud, Hisham Ben; Leong, Van Hong; Lestariono, Yuli

doi:10.1016/j.petlm.2019.04.002

Cited by 64 publications

(44 citation statements)

References 7 publications

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“…The FL model also follows the trend of the existing correlations (Fig 5), indicating the proper trend for the TT. The shorter TT implies that the sand is more consolidated [40]. Consequently, decreasing TT will increase the CTD.…”

Section: Trend Analysismentioning

confidence: 99%

A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells

et al. 2021

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Sand management is essential for enhancing the production in oil and gas reservoirs. The critical total drawdown (CTD) is used as a reliable indicator of the onset of sand production; hence, its accurate prediction is very important. There are many published CTD prediction correlations in literature. However, the accuracy of most of these models is questionable. Therefore, further improvement in CTD prediction is needed for more effective and successful sand control. This article presents a robust and accurate fuzzy logic (FL) model for predicting the CTD. Literature on 23 wells of the North Adriatic Sea was used to develop the model. The used data were split into 70% training sets and 30% testing sets. Trend analysis was conducted to verify that the developed model follows the correct physical behavior trends of the input parameters. Some statistical analyses were performed to check the model’s reliability and accuracy as compared to the published correlations. The results demonstrated that the proposed FL model substantially outperforms the current published correlations and shows higher prediction accuracy. These results were verified using the highest correlation coefficient, the lowest average absolute percent relative error (AAPRE), the lowest maximum error (max. AAPRE), the lowest standard deviation (SD), and the lowest root mean square error (RMSE). Results showed that the lowest AAPRE is 8.6%, whereas the highest correlation coefficient is 0.9947. These values of AAPRE (<10%) indicate that the FL model could predicts the CTD more accurately than other published models (>20% AAPRE). Moreover, further analysis indicated the robustness of the FL model, because it follows the trends of all physical parameters affecting the CTD.

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Section: Trend Analysismentioning

confidence: 99%

A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells

et al. 2021

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“…This leads to an increased concentration of suspended rock particles in produced liquid, causing submersible and surface equipment malfunctions. Resulting in a decreased well operation factor due to an increase in the frequency and duration of repairs and, as a result, in operating costs [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

An Investigation into Current Sand Control Methodologies Taking into Account Geomechanical, Field and Laboratory Data Analysis

et al. 2021

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Sand production is one of the major issues in the development of reservoirs in poorly cemented rocks. Geomechanical modeling gives us an opportunity to calculate the reservoir stress state, a major parameter that determines the stable pressure required in the bottomhole formation zone to prevent sand production, decrease the likelihood of a well collapse and address other important challenges. Field data regarding the influence of water cut, bottomhole pressure and fluid flow rate on the amount of sand produced was compiled and analyzed. Geomechanical stress-state models and Llade’s criterion were constructed and applied to confirm the high likelihood of sanding in future wells using the Mohr–Coulomb and Mogi–Coulomb prototypes. In many applications, the destruction of the bottomhole zone cannot be solved using well mode operations. In such cases, it is necessary to perform sand retention or prepack tests in order to choose the most appropriate technology. The authors of this paper conducted a series of laboratory prepack tests and it was found that sanding is quite a dynamic process and that the most significant sand production occurs in the early stages of well operation. With time, the amount of produced sand decreases greatly—up to 20 times following the production of 6 pore volumes. Finally, the authors formulated a methodological approach to sand-free oil production.

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“…The mechanism underpinning sand particles and fines interactions with scale inhibitor performance is difficult to understand. Sand production from unconsolidated formation reservoir is a very challenging problem as it ends the production life of a reservoir, and as well restricts the production flow rate [1].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the acidizing process reduces the compressive strength of the formation rock to weaken the consolidated formation for sand fines production to occur [3,4]. Selecting an appropriate technique for preventing formation sand production depends on different reservoir parameters, such as the sand prediction technique [1]. Others are resin and hydrogel chemical injection [5].…”

Section: Introductionmentioning

confidence: 99%

Effect of Produced Sand Particles and Fines on Scale Inhibitor: A Review

Anyanwu

Oluyemi

2021

Colloids and Interfaces

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Application of scale inhibitors in oil and gas production is aimed at mitigating scale blockage during production. Many experimental, mathematical, and numerical simulation modeling works have been carried out to evaluate behavior, performance, and interaction of the scale inhibitor chemicals within porous media in relation to their efficiency in solving scale problem. However, the mechanisms underpinning scale inhibitors performance are not well published. Some research works have shown theoretically that not all scale inhibitors pumped into the formation adsorb onto the formation rock. Some of the inhibitors may adsorb on produced loose sand grains or colloidal fine sand particles which float and flow within the pore spaces along with the scale inhibitor mostly in unconsolidated reservoirs This paper provides a review of research work on the effect of produced loose sand or colloidal fine particles flow on polyphosphonates and polyphosphinopolymer scale inhibitors performances during crude production.

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Sand production: A smart control framework for risk mitigation

Cited by 64 publications

References 7 publications

A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells

A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells

An Investigation into Current Sand Control Methodologies Taking into Account Geomechanical, Field and Laboratory Data Analysis

Effect of Produced Sand Particles and Fines on Scale Inhibitor: A Review

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