Abstract
Summary A proper field development plan require an accurate management of well placement respect the in-situ stresses. Understanding the stress status is a key factor toward any successful geomechanics model, which will guide the process of designing wells and integrate development, plans to minimize cost and maximize production. This paper represents a review of the present modelling ways of the in-situ stress variation laterally and vertically using the invented artificial intelligent tool that will assure geomechanics applications such as hydraulic fracking design, wellbore stability, well placement, and the mechanical behavior of the reservoir. Reservoir stresses are conducted from borehole image interpretation identifying drilling induced fractures and breakouts manually, depending principally on the experience and usually impacted by inconsistencies due to biased or unexperienced interpreters. Therefore, a robust automatic or semiautomatic approach was established to reduce time, manual efficiency and consistency. The current invention adding to the above geological and structural features, the calculation of the porosity and connectivity. The tool was successfully deployed to address a variety of challenging problems in BHI, and results showed an accurate detection of diverse and complex set of image attributes without manual intervention. The tool was tested and piloted for many wells, which concluded results exceeding 98% for full interpretation along with the analysis in less than one hour for an interval of 1000ft. This study describes and compare the different strategies of the far field from faults and well oriented from logs to predict the depth variation of stress within a layered rock formation and the impact on the stress orientation applied for Geomechanics modeling. The predictive strategies are based on well log data and in some cases on in situ stress measurements, combined with the weight of the overburden rock, the pore pressure, the depth variation in rock properties, and tectonic effects. These analyses were performed for stress profile construction and to calibrate the magnitudes of the horizontal stresses. To determine stress directions from automated borehole image interpretation data for subsequent comparison with stress directions inferred from the geomechanical models, a workflow was used based to infer Andersonian tectonic regime from stress analysis and comparing with the 1D Geomechanics models. In addition to detect SHmax and Shmin direction from breakouts or hydraulic fractures, borehole ovality, seismic anisotropy (including shear wave splitting etc.) and oriented cores. On top of that, interpret Shmin (at any specific depth) from extended leak-off tests or from the hydraulic fracture propagation pressure derived from mud-weight integration. Comparing the results with those from the fault plane solutions in restored sections, the intermediate principle stress can be calculated from the ratio of the least principal to intermediate stress as inferred from the tensile compressive transition in borehole wall. Finally, the presented approach can optimize placing wells correctly, hydraulic fractures applications and provide safe mud window.
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