This paper successfully applied the geoengineering workflow for integrated well-test analysis to characterize fluid flow in a newly discovered fractured reservoir in the Barents Sea. A reservoir model containing fractures and matrix was built and calibrated using this workflow to match complex pressure transients measured in the field. We outline different geological scenarios that could potentially reproduce the pressure response observed in the field, highlighting the challenge of non-uniqueness when analysing well-test data. However, integrating other field data into the analysis allowed us to narrow the range of uncertainty, enabling the most plausible geological scenario to be taken forward for more detailed reservoir characterization and history matching. The results provide new insights into the reservoir geology and the key flow processes that generate the pressure response observed in the field. This paper demonstrates that the geoengineering workflow used here can be applied to better characterize naturally fractured reservoirs. We also provide reference solutions for interpreting well tests in fractured reservoirs where troughs in the pressure derivative are recognizable in the data.@en

Fractures can be first-order controls on fluid flow in hydrocarbon reservoirs. Understanding the characteristics of fractures such as their aperture, density, distribution, conductivity, connectivity, etc, is key for reservoir engineering and production analysis. Well testing plays a key role in the the characterisation of fractured reservoirs, especially. New advances in the Pressure Transient Analysis (PTA) have enabled the interpretation of production data in a way where the resulting geological scenarios are in better agreement with fracture patterns observed in outcrop analogues. Traditionally, Drill Stem Test (DST) data have been the primay source of information for well testing. However, we hypothesise that wireline conveyed tools designed for Interval Pressure Transient Testing (IPTT) could yield a more throrough description of the near-wellbore heterogeneities, including fractures. Hence, we investigate the applicability of IPTT for characterising fractured reservoirs using detailed numerical simulations models with accurate wellbore representation to generate synthetic IPTT responses that can obtained through a next-generation wireline testing tool called SATURN. We particularly focus on cases where fractures are present in the near-wellbore region but do not intersect the wellbore. The study included parameters such as fracture densities and conductivities, distance between fractures and wellbore and the vertical extension of the fractures across geological beds. The impact of the different fracture scenarios on the pressure transient tests was recorded as characteristic signatures on diagnostic plots (pressure derivative curves). We have called these curves "IPTT-Geotypes"; they can be used to assist the interpretation process of IPTT responses. To the best of our knowledge, this is the first time pressure derivative type curves for IPTT in fractured reservoirs are presented in the literature. A field example of an IPTT case was analysed using the concept of geological well testing. We integrated the information from petrophysical logs and the IPTT-Geotypes to assist the calibration of a reservoir model developed to represent the geological setting of the tested reservoir interval. The results provided a sound interpretation of the reservoir geology and quantitative estimation of the matrix and fracture parameters.

@en

In this study we have applied new dual-porosity flow diagnostics to a recently discovered offshore fractured carbonate reservoir undergoing charactersiation studies. Carbonate reservoirs are typically highly hetrogeneous, naturally fractured and often mixed to oil wet, all of these factors are uncertain and can negatively impact upon recovery. With few wells drilled at the time of this study significant uncertainty hinders robust decision making. A robust multi-realisation approach is rendered impractical as the run time for a single realisation of the dual-porosity model is in excess of several days. Instead of using brute force we have utilised grid based flow diagnostics as a fast screening tool to select reservoir models for further full-physics simulations. The CPU time of flow diagnostics is almost negligable. Flow diagnostics are numerical tests perfomed on the static model that provide the time-of-flight, tracer partitions, drained/swept volumes and well pairs. In addition, dual-porosity metrics link the advective flow in the fractures to transfer from the matrix, indicating regions where flow and transfer are unbalanced and hence at risk of early breakthrough. Over 30 flow diagnostic tests were performed in under 10 minutes, the equivalent screening would take weeks using simulation. Results have shown that the fracture intensity and wettability are the most signifcant uncertainties that impact upon transfer and recovery, this effect would be missed by an equivalent single-porosity model. Well placement in this reservoir is very sensitive; the results show the proposed placement is effective for the assumed yet uncertain facies distribution. This broad sensitity screening has guided the ongoing modelling strategy, in partcular pinpointing the need for detailed characterisation of the fracture and facies distributions. Flow diagnostics are hence an excellent way to complement production forecasting workflows by providing a tool for quickly ranking and selecting scenarios for further detailed full-physics simulation, allowing us to focus more computational resources on reservoir models that are of particular interest.@en

A geological well testing model containing fractures and matrix was built to match an observed complex well test response in a reservoir that was known to be fractured. The resulting match of a well intersecting minor fractures near a major fracture was considered a good match in consideration of alternative geological scenarios. This match leads to a better understanding of the key reservoir features to reliably support development decisions

@en