Abstract
As unconventional reservoirs continue to be discovered and appraised, an ever increasing challenge is to understand the productive mechanism that unlocks the potential of these reservoirs. Since most unconventional reservoirs have some degree of lamination (varying from a few hundreds of an inch to a couple of feet), a technical hurdle exists in understanding the integration of conventional logging (using up-scaled measurements), modeling software (assumptions, gridding, numerical/P3D) and fine scale measurements (core measurements).
Laminated reservoirs pose many challenges in the decision making process especially when a model centric, data driven approach is utilized. These challenges can be reduced to two categories: (1) challenges in understanding fracture propagation mechanism and (2) challenges in reservoir characterization. This paper focuses on a procedure to capture the former. The early phase of gathering measurements is frequently executed with data sets and measurements that are incomplete and insufficient to understand the production mechanism in these low porosity environments. In an engineering analysis, this data may be utilized only to a limited extent, due to the inconsistences in the measurements gathered at various scales. To overcome these inconsistencies a novel approach to estimate mechanical properties with sub-sonic resolution through integration of sonic logs, high resolution logs, and facies classification has been developed.
The use of traditional workflows to derive mechanical properties has led to overestimating and/or underestimating rock strength and stress in the different layers. This, historically, has resulted in inconsistent conclusions across various disciplines and unexplainable well performance. Furthermore, the process of matching hydraulic fracture net-pressure using conventional workflows can result in the complication of fracture propagation process or incorrect calibration of the Mechanical Earth Model used to estimate earth stresses. We have demonstrated that the presented workflow allows for more accurate estimation of the mechanical properties profile in thin bed formations and consequently more effective use of those estimates to design hydraulic fractures and analyze the results.
