据海事新闻10月21日消息称，由于设备故障和损坏，全球范围内的计划外停机正在增加。规模较小的运营商没有多余的资金来进行相同水平的计划停机。

由于传统的设备故障预测方法在动态操作环境中不太可靠，因此除非绝对必要，否则它们可能无法批准重大的停机工作。

雷斯塔能源解释说：“因此，他们被迫经受住了运营的不确定性，不幸的是，意外停机增加了。”

计划外停机会给运营商带来严重的负面成本和生产后果。许多服务公司看到了这个有上升潜力的问题，现在转向科技公司，希望人工智能(AI)能够帮助解决这个问题，并最终增加收入。

雷斯塔能源预测，在油田服务行业中，人工智能在监测和预测设备故障方面的应用将继续上升。

曹海斌 摘译自 海事新闻

原文如下：

Oil Market to Depend on AI to Fix Downtime

Unplanned outages are on the rise globally from both equipment failures and damages. Smaller operators do not have the excess capital to conduct the same level of planned outages.

As traditional methods of predicting equipment failure can be unreliable in a dynamic operating environment, they can be hesitant to sanction significant shutdown work unless it is absolutely necessary.

"Thus, they are forced to ride out operational uncertainty and have unfortunately seen unplanned outages increase," explained Rystad Energy.

Unplanned outages have severe negative cost and production consequences for the operator. Viewing this problem with upside potential, many service companies are now turning to technology companies in the hopes that artificial intelligence (AI) can help solve the problem and, ultimately, to grow revenues.

Rystad Energy forecasts the application of artificial intelligence to monitor and predict equipment failures will continue to rise in the oilfield services industry.