A comparative study of filtration rate of water-based mud between silica and zinc oxide nanoparticles of different sizes for the deep well application

الملخص

In the oil and gas industry, drilling mud plays a vital role in the drilling process. However, during the drilling process, various factors such as the filtration process, the formation of a mud paste, and the pressure variation on the well walls can significantly impact the designs and complications in the well, in addition to changing the characteristics of the reservoir. One of the challenges in the drilling process is the leaching process, which can cause various problems including the rearrangement of pressure in the vicinity of the wellbore, swelling, and a variation in the strength characteristics of the rocks. These problems can lead to the insecurity of the wellbore, cavity formation, and precipitation. Therefore, it is crucial to displace the front reservoir fluid from the well and redistribute the pressure near the well to reduce the outflow risks of the well. To address these challenges, this study aims to analyze the filtration rate of water-based mud with silicon dioxide and zinc oxide nanoparticles. The water-based mud used in this study was made by combining various chemicals such as Caustic Soda (NaOH), Sodium Chloride (NaCl), Xanthan Gum, Starch, HT Starch, Calcium Carbonate (CaCO3), and Barite for usage in a deep well. In addition, different concentrations of HT starch with both silica and zinc oxide nanoparticles were also investigated. The drilling mud's filtration properties were determined using HPHT and API filter presses, which were used under very high pressure and high temperature (HPHT) and low pressure and low temperature (LPLT) conditions, respectively. The study found that nanoparticles provide better filtration rate performance as opposed to conventional mud. Notably, the use of zinc oxide and silicon dioxide nanoparticles reduced the HPHT filtration rate of conventional water-based mud by 26.2% and 52.3%, respectively.

الكلمات المفتاحية