Geostatistical seismic inversion and 3D modelling of metric flow units,porosity and permeability in Brazilian presalt reservoir

Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.

Graded and Quantitative Technology and Application of Coal-Bearing Reservoir Based on Seismic Reflection Characteristics

Taiyuan formation is the main exploration strata in Ordos Basin, and coals are widely developed. Due to the interference of strong reflection of coals, we cannot completely identify the effective reservoir information of coal-bearing reservoir on seismic data. Previous researchers have studied the reservoir by stripping or weakening the strong reflection, but it is difficult to determine the effectiveness of the remaining reflection seismic data. In this paper, through the establishment of 2D forward model of coal-bearing strata, the corresponding geophysical characteristics of different reflection types of coal-bearing strata are analyzed, and then the favorable sedimentary facies zones for reservoir development are predicted. On this basis, combined with seismic properties, the coal-bearing reservoir is quantitatively characterized by seismic inversion. The above research shows that the Taiyuan formation in LS block of Ordos Basin is affected by coals and forms three or two peaks in different locations. The reservoir plane sedimentary facies zone is effectively characterized by seismic reflection structure. Based on the characteristics of sedimentary facies belt and petrophysical analysis, the reservoir is semi quantitatively characterized by attribute analysis and waveform indication, and quantitatively characterized by pre stack geostatistical inversion. Based on the forward analysis of coal measure strata, this technology characterizes the reservoir facies belt through seismic reflection characteristics, and describes coal measure reservoirs step by step. It effectively guides the exploration of LS block in Ordos Basin, and has achieved good practical application effect.

Study on the Distribution of Interlayer in Thick Sandy Braided River under Large Well Spacing—A Case of C Oilfield in Bohai Sea

Using core, logging and other data, combined with field outcrop deposition, this paper studies the sedimentary genetic types and sedimentary stages of thick sandy braided river interlayer in C oilfield, and divides two stages of interlayer and three single-stage braided flow zones. On this basis, geostatistical inversion constrained by logging and discerning River quantitative knowledge base is carried out to predict the distribution range of the main interlayer in the two phases. The production performance test of the blind well and horizontal well shows that the coincidence rate of the prediction results of interlayer with thickness > 1.5 m is 75%. The research shows that the first stage is the main interlayer, mainly composed of mudstone of flood plain origin, with an average thickness of 2.1 m and relatively stable distribution. Based on the interlayer prediction results, the small layer of composite sand body 1 forms a residual oil enrichment area in the high part of the structure due to the wide range of interlayer shielding in the lower part, which is a favorable area for adjusting and tapping potential.

Spatial variability of soil chemical properties of Moso bamboo forests of China

This study investigates the spatial variability of soil organic matter(SOM),soil organic carbon(SOC)and pH in the upper 20-cm layer and 20-40 cm layer in Moso bamboo(Phyllostachys pubescens Pradelle)forests using a geostatistics model.Interpolation maps of SOM,SOC,and pH were developed using ordinary kriging(OK)and inverse distance weighted(IDW)methods.The pH,SOC,and SOM of the two soil layers ranged from 4.6 to 4.7,from 1.5 to 2.7 g kg^(-1)and from 20.3 to 22.4 g kg^(-1),respectively.The coefficient of variation for SOM and SOC was 29.9-43.3%while a weak variability was found for pH.Gaussian and exponential models performed well in describing the spatial variability of SOC contents with R^(2)varying from 0.95 to 0.90.The nugget/sill values of pH are less than 25%,which indicates a strong spatial correlation,while the nugget/sill values of SOC and SOM fall under moderate spatial correlation.Interpolation using ordinary kriging and inverse distance weighted methods revealed that the spatial distribution of SOM,SOC,and pH was inconsistent due to external and internal factors across the plots.Regarding the cross-validation results,the ordinary kriging method performed better than inverse distance weighted method for selected soil properties.This study suggests that the spatial variability of soil chemical properties revealed by geostatistics modeling will help decision-makers improve the management of soil properties.

Quality evaluation of glutenite reservoirs of intergranular-secondary dissolution pore type using a quantitative method

Glutenite(coarse-grained clastic)reservoirs of intergranularesecondary dissolution pore type are dominated by residual intergranular pores and secondary dissolution pores,and characterized by low porosity,low permeability,strong heterogeneity,and highly variable physical properties.It is difficult to conduct a quantitative quality assessment of these reservoirs while their primary control factors remain unclear.In this paper,experimental core data and drilling,logging and seismic data are used to assess the effect of sedimentary facies on reservoir quality.Favorable sedimentary facies zones are identified by analyzing the characteristics of glutenite reservoirs,which includes investigating rock components and their effects on reservoir quality.Argillaceous matrix content and rigid particle content are identified as the primary control factors for these reservoirs.Logging curves sensitive to reservoir quality are selected and examined to continuously characterize the physical parameters of the reservoirs.It establishes a calculation model of reservoir assessment parameters through multivariate regression and determines the quantitative assessment parameter Fr.The quality of the glutenite reservoirs is defined using conventional logging curves.This study also predicts the plane distribution of high-quality reservoirs through geostatistical inversion of the reservoir assessment parameters based on conventional wave impedance inversion,thus providing insight and guidance for quantitative assessment and quality prediction of glutenite reservoirs of the intergranular-secondary dissolution pore type.The application of this method to well deployment based on qualitative evaluation of the glutenite reservoirs in oilfields yielded favorable results.