Fluid evaluation and productivity prediction on complex reservoirs in Bozhong 19-6 structure

Kongdian Formation glutenite series and Archean metamorphic rock series in Bozhong 19-6 structure are characterized by complex reservoir lithologies and significant difference of reservoir physical properties, so it is difficult to identify the reservoir fluids, discriminate the oil and gas reservoir type and predict the early productivity. In this paper, the advantages of mud logging and logging parameters in the fluid evaluation and productivity prediction of complex reservoirs were tapped sufficiently. First, the properties of formation fluids were identified by combining Pixler chart, abnormal multiple, Bar diagram analysis method, Flair fluid index method, hydrocarbon abundance index method, rock mechanical parameter crossplot (Poisson's ratio and volume compressibility coefficient), and piezometric fluid regression analysis comprehensively. Second, the types of fluids in oil and gas reservoirs were discriminated by means of the phase state analysis method of components of fluids in well and the four-combined-parameter method. Third, as for low-porosity and low-permeability glutenite reservoirs, the stratigraphic model was established based on static data (e.g. logging, mud logging and core analysis), the oil reservoir parameters were calculated by using the dynamic data of wireline formation test and nuclear magnetic resonance (NMR), and accordingly the numerical simulation based productivity prediction method suitable for the complex reservoirs in Bozhong 19-6 structure was developed. Practice shows that by virtue of this combined method, the phase change characteristics of fluids in complex reservoirs can be identified effectively, the properties of reservoir fluids can be identified, and the types of fluids in oil and gas reservoirs can be discriminated. And when it is applied to low-porosity and low-permeability glutenite reservoirs, the productivity can be predicted accurately. It is verified from the final test conclusions that this combined method is reliable.