Improving drilling performance with continuous online measurements of electrical stability and conductivity in oil based drilling fluids

• It was developed an online device for electrical stability measurements.
• There is no similar available technology on the global market.
• Electrical stability is related to the stability of an inverted emulsion.
• Electrical stability is still only possible to be acquired via experimental test.
• The results demonstrated that the online device is adequate and operational.

Water-in-oil emulsions are commonly used as oil drilling fluids during drilling operations, therefore preventing emulsion breakage is imperative to maintain its viability and safety. An electrical stability test is able to provide important information regarding the emulsion state. While this is a common test performed by technicians in oil rigs, no technology has officially emerged on the market to perform such measurements in real time. In this work, experimental results of electrical stability were continuously acquired using a self-designed device and compared against results from bench tests according to API (American Petroleum Institute). Direct comparison with experimental results previously published by other authors was also used to validate its performance. The device was installed and tested in an automated drilling fluid production plant capable of making more than 4000 l/day of water or oil based fluids. In this plant, not only electrical stability was measured on line, but also pressure, flow rate, temperature, viscosity, density, solids content and size and water-in-oil ratio. Different oil/water compositions were tested as well as different values for oil based muds densities. The on line and bench test data showed agreement, as well as the tendencies observed in this work were in agreement with other authors results. A case study was undertaken where an uncontrolled water invasion was done simulating an operational problem commonly faced by drilling engineers during process. The outcomes of the case study proved and validated the importance of automation not only to improve overall performance, but also to predict and avoid costly operational problems due to early diagnosis.