Study On The Evaluation And Decision Support System For Oil Well Measures

Oil well measures is the production process of technological measures for increasing oil production, reservoir and enhance oil recovery rate. In recent years the oil fields have the same degree of their offensive production measures of workload, a series of technical measures, wash well fracturing, water plugging in oil well used, greatly improving the yield of the oil well, the effective mitigation of the oil yield of the natural decline rate. But at the same time, investment measures so that the production cost increases, partly block the economic benefits change for the worse, especially some measures for increasing oil ineffective or invalid, leads to a reduction of the overall economic benefits in production picks up at the same time of each oil field. Invalid input increasing, has become an important factor restricting the economic benefits of improving oil.Well, according to the evaluation measures will support measures after the evaluation and decision system of the sample management, single well time benefit of a single well thank optimization, prediction, single well secondary benefits block measures planning steps. Measures on measures of post evaluation is based optimization measures, prediction and planning, at the end of each period after the timely measures of the benefits of measures for evaluation, optimization, forecasting and planning measures to provide more learning samples. The benefit of data per well per cycle as a secondary benefit of single well sample. For heavy oil can be each steam injection cycle, for dilute oil can be each cycle of pump inspection cycle, some implementation measures, these periodic sample sample called measures, some cycle without the implementation of measures, these cycles of the sample is not the implementation of the measures of the sample, by the software system of automatic timing classification collation and management, but also can by manually revised. In measures before planning, first to the planning area of each well according to the comprehensive optimization of various indicators of a optimal measures, comprehensive indicators include:production data, economic data, risk data, three types of data, production data including:oil production, increase oil production, water cut, production days, including economic data:total cost, investment measures, investment recovery period, the risk of data including:the measure efficiency, economic efficiency, technology risk, production risk coefficient, coefficient of economic risk coefficient. The index is based on the statistical data of single well, statistical data reference block, and then optimized using grey correlation method, comprehensive consideration of various parameters. Automatic selection of optimal software system by the measures, artificial can be modified according to the experience.Forecast according to statistical measures planning parameters and measures to determine the effect of the selection of the objective function, establishes the corresponding measure programming model, system using genetic algorithm method to solve it, get the best configuration of various measures planning.