Research On Oil Bearing Evaluation Technology Of Fractured And Caved Mixed Carbonate Reservoir

Oil bearing evaluation is the key step of reservoir’s exploration and development, and the important indicator of evaluation. S block belongs to C basin in the west of China. In recent years the seismic survey information shows well trap geometry in its deep layer, and salt deposit distribution is the favorable cover, also the fault played the function of dredging. Well testing data shows that there are obvious oil shows in deep layer, thus it turns out to be high productivity layer. So research on S block deep layer’s oiliness is necessary.The main lithology of S block’s superficial layer is clastic rock, its middle layer is carbonate rock, and its deep layer is peperite reservoir which taken the carbonate as primary. The lithology changes a lot on the vertical. There are at least eight kinds of minerals in the reservoir, so each kind of rock or mineral’s incidence for oiliness is fuzzy. In order to find out the well reservoir belongs to which lithology, lithology identification need to be done for the total section. Firstly the LithoScanner data can be used to evaluating lithology, which processed of optimization could reflect the mineral content accurately, after compared with total rock diffraction data. Taking advantage of spectral log curve can fit out each mineral’s calculation model, so that mineral section of wells without LithoScanner data can be calculated. Secondly qualitative method can be adopted to discriminating lithology, such as crossplot analysis, logging curve property analysis and so on. Finally the pattern recognition method also can be used. Dividing the lithology into seven kinds, then extract each kind lithology’s eigenvalue of curve. Bayesian algorithm based on minimum error probability can calculate out one continuous square wave, and curve values stand for the depth point’s lithology.There are there kinds of reservoir space in research area, respectively are primary intergranular pore, secondary solution pore and fracture. These three kinds generally exist together, according to their combination feature, and combining with capacity and other data, the reservoir can be classified into four categories. Reservoir I is the best one, capacity is the highest, with the highest capacity, and complicated lithology. Reservoir Ⅳ is the worst, whose capacity is poor, and argillaceous content is more than other. Four pore structure model has been built base on four kinds of reservoirs, so that porosity character and electrical conductivity can be researched according to different classify.Reservoir with favorable porosity is the prerequisite of good oiliness, so calculations of these physical property parameters like porosity are very important.Calculation of shale content is mainly adopting the GR relative value, thorium relative value and acoustic wave method. Porosity is mainly adopting core calibration and volumetric model method. On the basis of lithology identification, makes the entire section rock matrix value change with lithology, which will be plugged into volumetric model for the porosity calculation. After building four kinds of multiple porosity structure models, discusses respectively porosity of matrix aperture, corrosion hole and fracture. Pore permeability’s computation can use the porosity fitting, and fracture width can be used to calculate fracture permeability. Stoneley waves that extracted from array sonic data can be used to calculate the total permeability of reservoir. Saturation is the key parameter of oiliness evaluation, so there are several algorithms of calculating saturation in this paper. Firstly the classical Archie’s formulas and the like have been used to calculate, but the result is unsatisfactory for the fractured reservoir. So the multiple pore structure models have been considered, the cementation index m changes with the different pore structure. Domestic scholar has proposed the electrical efficiency model, which also considered the pore structure’s influence for rock electrical conductivity into the model. So it’s appropriate for S block. Matching the relationship of electrical efficiency and porosity, then saturation can be figured out by electrical efficiency. Each physical property parameter’s lower limiting value can be confirmed according to oil production testing data from the research area.Presence of fractures can enhance the filtration capacity of reservoir, they are the good hydrocarbon migration pathways, and some of them can be the hydrocarbon pore volume. Therefore the layer grown a lot of effective fractures must be preferable reservoir, the number of fractures are positively related with oiliness, thus it’s important to recognizing fracture and cave. DLL data shows that it has the response for fracture and cave, so DLL data can be used to calculate fractured parameters by numerical simulation method. Imaging logging data can help recognize each kind of fractures more accurately, even include clearing layer structure feature, judging orientation of crustal stress, and using finite element method to calculate fractured parameters.In this paper, the author will give a comprehensive evaluation of reservoir oiliness from several aspects like lithology, reservoir space, fracture and physical property parameters that above mentioned, summarize a suit of effective complex reservoir oiliness evaluation technique.