The Method Research Based On Petrophysical Facies For Reservoir Evaluation On Low-porosity And Low-permeability Reservoir

With the deepening of the oil and gas field exploration and development, all kinds of complex oil and gas reservoirs have become the main exploration targets at present and even in the future.The low porosity and low permeability which is one of the complicated reservoir type has the huge development potential, which has become the focus of domestic and foreign oil and gas geology and development experts are concerned. So reservoir evaluation and description have become one of the most key technology issues. It is difficult to explore and develop the low-porosity and low-permeability reservoir at present. There are lots of difficulties in well logging interpretation and evaluation of low-porosity and low-permeability reservoir also, such as the exact calculation of porosity and saturation, the distinguish of oil(gas) and water zone according to electric logging, the identification of porosity gas zone, the prediction of productivity, and others. Compared with the conventional reservoir, the computation accuracy of reservoir parameters and the coincidence rate of logging interpretation are lower. Therefore, it is significant to continue the study of well logging interpretation and the evaluation in low-porosity and low-permeability reservoir for theory and practical application.The study area is a typical low porosity, low permeability sandstone reservoir, There are the development of faults in the area, many types of reservoirs, complicated distribution of oil and water and no uniform oil-water interface. This study is based on the full study of the special geological conditions in the region, analysis of logging data, and core analysis, mercury injection data and so on, combined with the existing logging interpretation and evaluation technology, launched comprehensive reservoir evaluation, building up the interpretation model more accurately, obtain the reservoir parameters contain porosity, permeability, flow zone index which in related to the reservoir rock and physical facies, which dividing the Petrophysical facies for the core well, distinguishing the types of reservoir with mathematical method, the pattern recognition method. At last, this paper identifies and predicts Petrophysical facies for noncoring well on the basis of distinguish. The main contents of this paper are as follows:(1) According to the actual situation of low porosity and low permeability reservoir, this paper researches the lithologic characteristic, physical property, electrical property, oil-bearing characteristics and pore structure characteristics of reservoir and analyses the "four property" relations with the basis of the core analysis data which contains physical, mercury injection, and thin slice, combining the well logging data at the same time,.(2) According to the problem that the low porosity and low permeability reservoir parameter calculation precision is insufficient.The paper put forward the concept of the petrophysical facies, which through FZI (flow zone index) to distinguish quantitatively petrophysical facies.Through the porosity and permeability interpretation model under the restriction of petrophysical facies, it can better solve the reservoir lithology diversification and the complicated pore structure, etc problems, which lead to the interpretation more accurate than traditional methods.(3) This paper analyses different methods to classify petrophysical facies. It points out the defect of the classification using FZI (flow zone index), and it develops several modifying approach. As an effective technical clue that developing fine logging interpretation and evaluation in low-porosity and low-permeability reservoir is adopted in this paper, and it applies the petrophysical facies classification and prediction in low-porosity and low-permeability reservoir. To improve the problem using FZI in petrophysical facies classification, it carries out the following work process:first, classifying the petrophysical facies using FZI with the restraint of petrophysics in coring formation; then developing the relations between the classification of petrophysical facies and logging data by fuzzy clustering and principal component analysis and discriminant method; last, predicting the classification of petrophysical facies with the relations in no coring formation.(4) This paper sets up the reservoir parameter computation model according to the petrophysical facies classification, and then computes the reservoir parameters basing on the prediction of petrophysical facies classification in formation According to the cross plot analysis and error calculation, the computation accuracy of reservoir parameters according to petrophysical facies is higher than that of ignoring petrophysical facies classification evidently. And the model also obtains good result in the practical application.(5) This paper identifies the fluid type and evaluates the reservoir on basen of the calculated reservoir parameters, the analysis result of rock pore structure and the test data and other data.