In drilling industries, hydraulic fracturing of unconventional shale-gas wells is a highly industrialized process involving multiple equipment, substances, and operational stages. However, fracturing operations also involve extremely hazardous work relating to high-pressure chemicals, heavy equipment, and flammable gases. During the fracturing process, human error frequently causes sand blockages, equipment damage, and fracturing fluid leakage. An assessment of human error likelihood is essential for the prevention of resulting incidents, and thereby improving the safety and stability of the entire shale-gas fracturing operations. However, due to the latency, unpredictability, and variety of human errors in fracturing operations, previous studies have not sufficiently considered uncertainties. Hence, an integrated method that applies the UAHP-SPA model is proposed to assess human error likelihood in the fracturing process. The indexes of human error likelihood assessment in fracturing operations are first established based on 4M theory. Then, the Set Pair Analysis (SPA) technique is used to consider epistemic uncertainties from assessed objects, assessment procedures, assessor subjectivities, and incomplete data. Furthermore, the SPA-based Uncertainty Analytic Hierarchy Process (UAHP) is applied for reducing aleatory uncertainties in the index weight optimization. The proposed method is able to effectively provide static likelihood states and dynamic likelihood trends of various human errors. To illustrate its validity, an on-site fracturing operator is selected as a test case. Results show that this UAHP-SPA model is more accurate and practical compared to conventional approaches. (C) 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.