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Unconsolidated reservoirs on Kikinda oil field cause sanding issues, which complicate exploiting of the wells. As a result, predicting critical depression above which intensive sand production commences becomes substantial problem to solve. 1D-geomechanical wellbore stability models were used as a tool to evaluate critical depressions on production wells. The fundamental complicacy in modeling was the poorly preserved core, so that it was impossible to conduct rock strength tests. Therefore, the approach to solve inverse problem approach was investigated. It allows determining formation strength from completions, historical production data and production initiating tests. Input data for modeling included standard set of logs (resistivity, gamma, neutron, acoustic (compressional wave velocity)); shear wave velocity recovered by means of a neural network, mini-fracturing data was used in matching the value of minimum horizontal stress. The correlation between the strength of uniaxial compression and elastic modulus was derived from matching the modelled profile of cavities with caliper log in conjunction with historical data. There were two ways to confirm the models. The first was by production initiation tests on pre-targeted depressions for new intervals along with sand production monitoring. The second was by calculating depression and comparing with predicted value for previously perforated intervals (where data was available), that is retrospective analysis. According to historical data, the wells equipped with filters and gravel pack systems have 1000 days less mean time before failure (MTBF) than the wells that flow freely on subcritical depressions. Moreover, filters, presenting supplementary obstacle for fluid, often result in high skin values up to 40-80. At the same time, to reduce risks of needing the next workover gravel packs are being installed on the vast majority of the wells. It is possible to indentify relatively firm intervals with high critical depressions and design their completions excluding the installation of filtering equipment. As a result, well performance could be improved. Conducted evaluations juxtaposed with production tests showed that solving the inverse problem approach allows utilizing geomechanical models in critical depression estimation for pay intervals. The main uncertainty of the technique is associated with low accuracy of forecasts for intensively flushed intervals. Supplementary studies on how high watercut influences rock strength was beyond the scope of the project. To sum up, the approach of solving the inverse problem was introduced to predict sand production problems for the complex F on Kikinda oil field. The methodology incorporates rock strength determination based on caliper log and production history data. The advantage of the technique is the possibility to carry out evaluations even in the absence of core geomechanical tests data. |
