Identification of watered-out zones in carbonate reservoirs using resistivity curve reconstruction based on reservoir classification

The KT-II layer in the Zananor Oilfield,Caspian Basin,Kazakhstan,contains carbonate reservoirs of various types.The complex pore structure of the reservoirs have made it difficult to identify watered-out zones with traditional logging interpretation methods.This study classifies the reservoirs on the basis of core analysis and establishes an identification model for watered-out layers in the field to effectively improve the interpretation accuracy.Thin section analysis shows that there are three types of pores in the reservoirs,i.e.,the matrix pore,fracture and dissolution vug.A triple porosity model is used to calculate the porosities of the reservoirs and the results are combined with core analysis to classify the reservoirs into the fractured,matrix pore,fracture-pore as well as composite types.A classification standard is also proposed.There are differences in resistivity logging responses from the reservoirs of different types before and after watering-out.The preewatering-out resistivities are reconstructed using generalized neural network for different types of reservoirs.The watered-out layers can be effectively identified according to the difference in resistivity curves before and after watering-out.The results show that the watered-out layers identified with the method are consistent with measured data,thus serving as a reference for the evaluation of watered-out layers in the study area.

Quantitative Method of Classification and Discrimination of a Porous Carbonate Reservoir Integrating K-means Clustering and Bayesian Theory

Reservoir classification is a key link in reservoir evaluation.However,traditional manual means are inefficient,subjective,and classification standards are not uniform.Therefore,taking the Mishrif Formation of the Western Iraq as an example,a new reservoir classification and discrimination method is established by using the K-means clustering method and the Bayesian discrimination method.These methods are applied to non-cored wells to calculate the discrimination accuracy of the reservoir type,and thus the main reasons for low accuracy of reservoir discrimination are clarified.The results show that the discrimination accuracy of reservoir type based on K-means clustering and Bayesian stepwise discrimination is strongly related to the accuracy of the core data.The discrimination accuracy rate of TypeⅠ,TypeⅡ,and TypeⅤreservoirs is found to be significantly higher than that of TypeⅢand TypeⅣreservoirs using the method of combining K-means clustering and Bayesian theory based on logging data.Although the recognition accuracy of the new methodology for the TypeⅣreservoir is low,with average accuracy the new method has reached more than 82%in the entire study area,which lays a good foundation for rapid and accurate discrimination of reservoir types and the fine evaluation of a reservoir.

Integrated classification method of tight sandstone reservoir based on principal component analysise simulated annealing genetic algorithmefuzzy cluster means

In this research,an integrated classification method based on principal component analysis-simulated annealing genetic algorithm-fuzzy cluster means(PCA-SAGA-FCM)was proposed for the unsupervised classification of tight sandstone reservoirs which lack the prior information and core experiments.A variety of evaluation parameters were selected,including lithology characteristic parameters,poro-permeability quality characteristic parameters,engineering quality characteristic parameters,and pore structure characteristic parameters.The PCA was used to reduce the dimension of the evaluation pa-rameters,and the low-dimensional data was used as input.The unsupervised reservoir classification of tight sandstone reservoir was carried out by the SAGA-FCM,the characteristics of reservoir at different categories were analyzed and compared with the lithological profiles.The analysis results of numerical simulation and actual logging data show that:1)compared with FCM algorithm,SAGA-FCM has stronger stability and higher accuracy;2)the proposed method can cluster the reservoir flexibly and effectively according to the degree of membership;3)the results of reservoir integrated classification match well with the lithologic profle,which demonstrates the reliability of the classification method.

Classification of tight sandstone reservoirs based on NMR logging

The traditional reservoir classification methods based on conventional well logging are inefficient for determining the properties,such as the porosity,shale volume,J function,and flow zone index,of the tight sandstone reservoirs because of their complex pore structure and large heterogeneity.Specifically,the method that is commonly used to characterize the reservoir pore structure is dependent on the nuclear magnetic resonance(NMR)transverse relaxation time(T2)distribution,which is closely related to the pore size distribution.Further,the pore structure parameters(displacement pressure,maximum pore-throat radius,and median pore-throat radius)can be determined and applied to reservoir classification based on the empirical linear or power function obtained from the NMR T2 distributions and the mercury intrusion capillary pressure ourves.However,the effective generalization of these empirical functions is difficult because they differ according to the region and are limited by the representative samples of different regions.A lognormal distribution is commonly used to describe the pore size and particle size distributions of the rock and quantitatively characterize the reservoir pore structure based on the volume,mean radius,and standard deviation of the small and large pores.In this study,we obtain six parameters(the volume,mean radius,and standard deviation of the small and large pores)that represent the characteristics of pore distribution and rock heterogeneity,calculate the total porosity via NMR logging,and classify the reservoirs via cluster analysis by adopting a bimodal lognormal distribution to fit the NMR T2 spectrum.Finally,based on the data obtained from the core tests and the NMR logs,the proposed method,which is readily applicable,can effectively classify the tight sandstone reservoirs.

Genesis and microscopic characteristics of tight reservoirs in the Fengcheng Formation, at the southern margin of the Mahu Sag

The tight reservoirs of the Fengcheng Formation at the southern margin of the Mahu Sag have strong heterogeneity due to the diversity in their pore types, sizes, and structures. The microscopic characteristics of tight reservoirs and the mechanisms that generate them are of significance in identifying the distribution of high-quality reservoirs and in improving the prediction accuracy of sweet spots in tight oil reservoirs. In this paper, high-pressure mercury intrusion (HPMI) and nuclear magnetic resonance (NMR) experiments were carried out on samples from the tight reservoirs in the study area. These experimental results were combined with cluster analysis, fractal theory, and microscopic observations to qualitatively and quantitatively evaluate pore types, sizes, and structures. A classification scheme was established that divides the reservoir into four types, based on the microstructure characteristics of samples, and the genetic mechanisms that aided the development of reservoir microstructure were analyzed. The results show that the lower limit for the tight reservoir in the Fengcheng Formation is Φ of 3.5% and K of 0.03 mD. The pore throat size and distribution span gradually decrease from Type I, through Type II and Type III reservoirs to non-reservoirs, and the pore type also evolves from dominantly intergranular pores to intercrystalline pores. The structural trend shows a decrease in the ball-stick pore-throat system and an increase in the branch-like pore-throat system. The dual effects of sedimentation and diagenesis shape the microscopic characteristics of pores and throats. The sorting, roundness, and particle size of the original sediments determine the original physical properties of the reservoir. The diagenetic environment of ‘two alkalinity stages and one acidity stage’ influenced the evolution of pore type and size. Although the cementation of authigenic minerals in the early alkaline environment adversely affected reservoir properties, it also alleviated the damage of the later compaction to some extent. Dissolution in the mid-term acidic environment greatly improved the physical properties of this tight reservoir, making dissolution pores an important reservoir space. The late alkaline environment occurred after large-scale oil and gas accumulation. During this period, the cementation of authigenic minerals had a limited effect on the reservoir space occupied by crude oil. It had a more significant impact on the sand bodies not filled with oil, making them function as barriers.

Integrated petrophysical log characterization for tight carbonate reservoir effectiveness: A case study from the Longgang area, Sichuan Basin, China

Ultra-low porosity and permeability, inhomogeneous fracture distribution, and complex storage space together make the effectiveness evaluation of tight carbonate reservoirs difficult. Aiming at the carbonate reservoirs of the Da＇anzhai Formation in the Longgang area of the Sichuan Basin, based on petrophysical experiments and logging response characteristics, we investigated the storage properties of matrix pores and the characteristics of fracture development to establish a method for the characterization of effectiveness of tight reservoirs. Mercury injection and nuclear magnetic resonance （NMR） experiments show that the conventional relationship between porosity and permeability cannot fully reflect the fluid flow behavior in tight matrix pores. Under reservoir conditions, the tight reservoirs still possess certain storage space and permeability, which are controlled by the characteristic structures of the matrix porosity. The degree of fracture development is crucial to the productivity and quality of tight reservoirs. By combining the fracture development similarity of the same type of reservoirs and the fracture development heterogeneity in the same block, a three-level classification method of fracture development was established on the basis of fracture porosity distribution and its cumulative features. According to the actual production data, based on the effectiveness analysis of the matrix pores and fast inversion of fracture parameters from dual laterolog data, we divided the effective reservoirs into three classes： Class I with developed fractures and pores, and high-intermediate productivity; Class II with moderately developed fractures and pores or of fractured type, and intermediate-low productivity; Class III with poorly developed fractures and matrix pores, and extremely low productivity. Accordingly log classification standards were set up. Production data shows that the classification of effective reservoirs is highly consistent with the reservoir productivity level, providing a new approach for the effectiveness evaluation of tight reservoirs.