A Study on Identification of Conglomerate Reservoir Parameters and Oil/Water Beds in Ke82 Well Areas of Junggar Basin

This paper is mainly about the calculation of reservoir parameters and theinterpretation method for identifying oil/water beds in Ke82 well areas of Junggar basin. It isdifficult to determine the reservoir parameters with common logging methods such as core calibrationlog because of the diversity of minerals and rocks and the complexity of pore structures in theconglomerate reservoir of Junggar basin. Optimization logging exploration is a good method todetermine the porosity by establishing the multi-mineral model with logging curves based on theintegration of geological, core and well testing data. Permeability is identified by BP algorithm ofneural network. Hydrocarbon saturation is determined by correlating Archie's and Simandouxformulas. Comparing the exploratory result and core data, we can see that these methods areeffective for conglomerate logging exploration. We processed and explained six wells in the Ke82well areas. And actual interpretation has had very good results, 85 % of which conform to welltesting data. Therefore, this technique will be effective for identifying conglomerate parameters.

The constructing of pore structure factor in carbonate rocks and the inversion of reservoir parameters

With a more complex pore structure system compared with clastic rocks, carbonate rocks have not yet been well described by existing conventional rock physical models concerning the pore structure vagary as well as the influence on elastic rock properties. We start with a discussion and an analysis about carbonate rock pore structure utilizing rock slices. Then, given appropriate assumptions, we introduce a new approach to modeling carbonate rocks and construct a pore structure algorithm to identify pore structure mutation with a basis on the Gassmann equation and the Eshelby-Walsh ellipsoid inclusion crack theory. Finally, we compute a single well＇s porosity using this new approach with full wave log data and make a comparison with the predicted result of traditional method and simultaneously invert for reservoir parameters. The study results reveal that the rock pore structure can significantly influence the rocks＇ elastic properties and the predicted porosity error of the new modeling approach is merely 0.74%. Therefore, the approach we introduce can effectively decrease the predicted error of reservoir parameters.

Reservoir parameter inversion based on weighted statistics

Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.

Effect of gas saturation on P-wave velocity in tight sandstone

By measuring the variation of the P-and S-wave velocities of tight sandstone samples under water saturation,it was confirmed that with the decrease in water saturation,the P-wave velocity first decreased and then increased.The variation in velocity was influenced by the sandstone’s porosity.The commonly used Gassmann equation based on fluid substitution theory was studied.Comparing the calculated results with the measured data,it was found that the Gassmann equation agreed well with the measured data at high water saturation,but it could not explain the bending phenomenon of P-wave velocity at low saturation.This indicated that these equations could not accurately describe the relationship between fluid content and rock acoustic velocity.The reasons for this phenomenon were discussed through Taylor’s expansion.The coefficients of the fitting formula were calculated and verified by fitting the measured acoustic velocity changes of the cores.The relationship between P-wave velocity and saturation was discussed,which provides experimental support for calculating saturation using seismic and acoustic logging data.

3D Slicing of Weighted Index for Reservoir Quality of Lower Miocene Rocks, Belayim Marine Oil Field, Gulf of Suez, Egypt

This study aims to have a single coefficient resulting from the integration of all the reservoir parameters through which a decision can be taken to determine the best quality places in the reservoir. The conventional well logging data in nine wells were used to determine the reservoir parameters in the study area. Seven different parameters were calculated, five of them were directly proportional to the quality of the reservoir, while the remaining two parameters which represent shale volume and water saturation were inversely proportional to the reservoir quality. The index of each parameter was calculated. A new value was created from the integration of the seven different parameter indexes called the weighted index for the reservoir quality. The reservoir quality values were sliced in the three dimensions depending on the effect of all reservoir parameters and not on any single parameter. It is clear from the results of this study that horizontal and vertical slicing, as well as cut-off values, illustrates that the middle and upper parts are the best places for the reservoir to explore hydrocarbons, where the values of the weighted index of the reservoir quality range from 0.65 to 0.9. Meanwhile, the quality of the reservoir decreases in its lower parts.

Log identification method in complex sand reservoirs

In order to obtain effective parameters for complex sand reservoirs,a log evaluation method for relevant reservoir parameters is established based on an analysis in the gas-bearing sandstone with high porosity and low permeability,low porosity and permeability and on various characteristics of log responses to reservoir lithologies and physical properties in the Neopleozoic sand reservoir of the Ordos basin.This log evaluation method covers the Cook method that is used to evaluate the porosity and oiliness in high porosity and low permeability reservoirs and another method in which the mineral content,derived from geochemical logs,is used to identify formation lithologies.Some areas have high calcium and low silt content,not uniformly distributed,the results of which show up in the complex formation lithologies and conventional log responses with great deviation.The reliability of the method is verified by comparison with conventional log data and core analyses.The calculation results coincide with the core analytical data and gas tests,which indicate that this log evaluation method is available,provides novel ideas for study of similar complex reservoir lithologies and has some reference value.

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.

A smart productivity evaluation method for shale gas wells based on 3D fractal fracture network model

The generation method of three-dimensional fractal discrete fracture network(FDFN)based on multiplicative cascade process was developed.The complex multi-scale fracture system in shale after fracturing was characterized by coupling the artificial fracture model and the natural fracture model.Based on an assisted history matching(AHM)using multiple-proxy-based Markov chain Monte Carlo algorithm(MCMC),an embedded discrete fracture modeling(EDFM)incorporated with reservoir simulator was used to predict productivity of shale gas well.When using the natural fracture generation method,the distribution of natural fracture network can be controlled by fractal parameters,and the natural fracture network generated coupling with artificial fractures can characterize the complex system of different-scale fractures in shale after fracturing.The EDFM,with fewer grids and less computation time consumption,can characterize the attributes of natural fractures and artificial fractures flexibly,and simulate the details of mass transfer between matrix cells and fractures while reducing computation significantly.The combination of AMH and EDFM can lower the uncertainty of reservoir and fracture parameters,and realize effective inversion of key reservoir and fracture parameters and the productivity forecast of shale gas wells.Application demonstrates the results from the proposed productivity prediction model integrating FDFN,EDFM and AHM have high credibility.

Prediction of rock brittleness using nondestructive methods for hard rock tunneling

Sand production is an undesired phenomenon occurring in unconsolidated formations due to shear failure and hydrodynamic forces. There have been many approaches developed to predict sand production and prevent it by changing drilling or production strategies. However, assumptions involved in these approaches have limited their applications to very specific scenarios. In this paper, an elliptical model based on the borehole shape is presented to predict the volume of sand produced during the drilling and depletion stages of oil and gas reservoirs. A shape factor parameter is introduced to estimate the changes in the geometry of the borehole as a result of shear failure. A carbonate reservoir from the south of Iran with a solid production history is used to show the application of the developed methodology. Deriving mathematical equations for determination of the shape factor based on different failure criteria indicate that the effect of the intermediate principal stress should be taken into account to achieve an accurate result. However, it should be noticed that the methodology presented can only be used when geomechanical parameters are accurately estimated prior to the production stage when using wells and field data.

An Integrated Mass Balance Approach for Assessing Hydrocarbon Resources in a Liquid-Rich Shale Resource Play:An Example from Upper Devonian Duvernay Formation,Western Canada Sedimentary Basin

Petroleum resource assessment using reservoir volumetric approach relies on porosity and oil/gas saturation characterization by laboratory tests.In liquid-rich resource plays,the pore fluids are subject to phase changes and mass loss when a drilled core is brought to the surface due to volume expansion and evaporation.Further,these two closely related volumetric parameters are usually estimated separately with gas saturation inferred by compositional complementary law,resulting in a distorted gas to oil ratio under the circumstances of liquid hydrocarbon loss from sample.When applied to liquid-rich shale resource play,this can lead to overall under-estimation of resource volume,distorted gas and oil ratio(GOR),and understated resource heterogeneity in the shale reservoir.This article proposes an integrated mass balance approach for resource calculation in liquid-rich shale plays.The proposed method integrates bulk rock geochemical data with production and reservoir parameters to overcome the problems associated with laboratory characterization of the volumetric parameters by restoring the gaseous and light hydrocarbon loss due to volume expansion and evaporation in the sample.The method is applied to a Duvernay production well(14-16-62-21 W5)in the Western Canada Sedimentary Basin(WCSB)to demonstrate its use in resource evaluation for a liquid-rich play.The results show that(a)by considering the phase behavior of reservoir fluids,the proposed method can be used to infer the quantity of the lost gaseous and light hydrocarbons;(b)by taking into account the lost gaseous and light hydrocarbons,the method generates an unbiased and representative resource potential;and(c)using the corrected oil and gas mass for the analyzed samples,the method produces a GOR estimate close to compositional characteristics of the produced hydrocarbons from initial production in 14-16-62-21 W5 well.