The purpose of this paper is to impart the development of a Process-Knowledge Management System (P-KMS) designed to investigate drilling in gas hydrate environments, identify potential well risks (well control, borehole stability and/or well integrity), and assess mitigation of them due to alteration of drilling parameters and/or strategies. Since successful drilling in gas hydrates environments is influenced strongly by numerous parameters and relations that are sometimes ill-defined, or not understood properly, the P-KMS developed needs to permit users the ability to update the knowledge utilized, as well as handle uncertainty as multidimensional phenomena. For this, traditional engineering simulations and uncertainty handling by soft computing have been combined in a novel approach with knowledge management paradigms. This allows the inclusion of knowledge from multiple field experts, and its combination with approved company best practices and guidelines. In order to consider the uncertainties associated with knowledge, approximate reasoning by type-2 fuzzy logic is combined with relevant numerical simulations (pressure and temperature fields, thermodynamic and kinetic gas hydrate behavior). This combination of knowledge is established by the P-KMS through the construction of individual reasoning blocks and a coherent reasoning lattice. Because expert knowledge (expressed in rules and equations) and standard engineering calculations are combined in a modular form, updating of knowledge, as well as well situation-specific applications of it, are assisted. The P-KMS can be applied in two reasoning modes, either for dynamic process assessment (simulation mode) or static well situation analysis (parameter inference mode). During reasoning, uncertainties employed are monitored constantly in such a way that knowledge gap identification and system performance evaluation is supported. Consequently, it is anticipated that using such a P-KMS approach will lead to (1) increase in well-site security, (2) reduction of overall well costs, and (3) creation of experience in development, implementation and maintenance of a P-KMS for similar problem areas.