With the rising consumption of oil resources, major oil companies around the world have increasingly engaged in offshore oil exploration and development, and offshore oil resources have accounted for an increasing proportion. Offshore oil engineering projects are capital intensive, and the development of offshore oil fields faces a tough battle, especially in a period of low oil prices. Thus, a comprehensive evaluation model is highly needed to help assess economic benefits and provide meaningful and valuable information for operators and investors to make sensible decisions. This study firstly proposed a realistic and integrated evaluation model for offshore oil development based on actual historical project data. This evaluation model incorporated modules from the underwater system to the platform system and processes from oil reservoir extraction to oil, gas and water treatment. The uncertain parameters in the evaluation process are dealt with by sensitivity analysis and Monte Carlo simulation. The proposed model is applied to a typical offshore oil development project in Bohai Bay, China. The results reveal that the recovery factor and oil price have the greatest impact on the economic benefits. In the case of deterministic analysis, the breakeven oil price of the project is 40.59 USD/bbl. After considering the uncertainty of project parameters, the higher the oil price, the greater the probability of NPV > 0. When the oil price is higher than 70 USD/bbl, even with uncertain project parameters, the probability of NPV > 0 can still be as high as 97.39%.

Drilling and logging are important links in oil and gas development, and the accurate acquisition of operation data directly affects the development efficiency of oil and gas reserves. Under the dual pressure of safety and economy, it is essential to find out how to improve the quality of logging, especially the quality of logging while drilling. This article focuses on logging technology applied in the Bohai Bay field. Drilling engineering data from several sites are analyzed to identify factors influencing the reliability performance of formation pressure tests. The analysis is conducted using the commercial drilling engineering software JewelSuite. Two types of main failure phenomena are summarized: lost seal, time out. Next, logging reliability improvement technologies are proposed based on the results of reliability analysis, such as resolution improvement, bottom hole assembly optimization, and on‐site construction operation procedures. These technologies can achieve more efficient and accurate formation pressure acquisition while providing important data for later productivity prediction and development. The practice has proved that the improved technologies can reduce failures by nearly 66.7%, and can also reduce cost by more than 33.84 M USD.

Unmanned aerial vehicle (UAV) provides the possibility of comprehensive coverage and multi-dimensional visualization of pipeline monitoring. Currently, the research on UAV path planning begins to emerge under the encouragement of industry policies in China. The target of UAV path planning in pipeline network inspection is to design a flight path with the least cost in advance. The