The well design with long lateral section and multistage frac completion has been proven effective for development of the unconventional reservoirs. Top-tier well production in unconventional reservoir can be achieved by optimizing hydraulic completion and stimulation design, which necessitates an understanding of flow behavior and hydrocarbon contribution allocation.  Historically, conventional production logging (PL) surveys were scarcely used in unconventional reservoirs due to limited and often expensive conveyance options, as well as complicated and non-unique inflow interpretations caused by intricate and changing multi-phase flow behavior (Prakash et al., 2008). The assessment of the cluster performance gradually shifted towards distributed acoustic (DAS) and temperature (DTS) sensing methods using fiber optics cable, which continuously gained popularity in the industry. Fiber optics measurements were anticipated to generate production profiles along the lateral with sub-cluster resolution to assist with optimal completions design selection. Encapsulation of the fiber in the carbon rod provided alternative conveyance method for retrievable DFO measurements, which gained popularity due to cost-efficiency and operational convenience (Gardner et al., 2015). Recent utilization of micro-sensor technology in PL tools, (Abbassi et al, 2018, Donovan et al, 2019) allowed dramatic reduction of the size and the weight of the PL toolstring without compromising wellbore coverage by sensor array. Such ultra-compact PL toolstring could utilize the carbon rod as a taxi and provide mutually beneficial and innovative surveillance combination to evaluate production profile in the unconventional reservoirs. Array holdup and velocity measurements across wellbore from PL would reveal more details regarding multi-phase flow behavior, which could be used for cross-validation and constraining of production inflow interpretation based on DFO measurements. This paper summarizes the lessons learned, key observations and best practices from the unique 4 well program, where such innovative combination was tested in gas rich Duvernay shale reservoir.

Oil spill risks associated with oil and gas exploration and production are changing as industry moves to deeper water. Computer-based modeling is typically used to quantify the fate and trajectory of sub sea releases (e.g., well blowouts). Stochastic modeling has become common as computational resources have grown, allowing for a large number of combinations of met ocean parameters to be evaluated. Simulating many potential realizations of a single discharge event allows for the calculation of spatially varying probabilities of oiling due to natural variability in the prevailing wind and current, but this needs to be treated separately from the likelihood of the sub sea release occurring to appropriately evaluate the oil spill risks of the offshore activity. Some industry guidance explicitly recognizes that the likelihood of a discharge event occurring is independent of the natural variability of the environmental setting and correctly treat these items as statistically independent; however, this distinction is sometimes lost in practice. In these instances, the resulting oil spill risk assessments may inadvertently be based on highly improbable combinations of release conditions and met ocean forcing. A transparent and robust risk-based oil spill risk assessment needs to explicitly communicate the differences between the likelihood of a release event occurring and the probabilities of the potential trajectories that could result under different combinations of met ocean parameters. This poster uses a hypothetical deepwater blowout to illustrate how stochastic and deterministic modeling can be combined to characterize the probability distribution associated with the (variable) potential consequence of a discharge event. The proposed modeling strategy allows for the set of trajectories generated by stochastic modeling to be ranked based on various metrics of interest (e.g., volume of water column swept, area of surface slick, or volume of oil ashore) so the distribution of potential consequence can be evaluated. Following recently industry guidance (IPECA-OGP), it is suggested that the most probably deterministic trajectory be paired with statistical analysis, although the strategy allows for an identifiable amount of conservatism to be incorporated into the analyses by selecting one or more other trajectories for detailed impacts assessment.