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Permeability is one of the important reservoir properties for oil and gas reservoirs. It directly impacts the reservoir's ability to produce and is considered a key factor to delineate reservoir sweet spots for optimum well placement and successful development strategies. However, the permeability prediction is difficult for coal seam gas (CSG) reservoirs due to the presence of complex geological conditions which cause the lateral and vertical heterogeneity on the coal seam. The objective of this study is to present a practical petrophysical approach where the estimation of coal permeability is possible under the mapping of fractures and cleats using high-resolution microresistivity image logging data. This technique provides meaningful results that can integrate better with known coal geological criteria such as ranking and lithotypes. Furthermore, it helps better analyze production data and enhance history matching calibration. Post-processing technique using resistivity inversion model and mud filtrate resistivity allowed to calculate fractures and cleats aperture as well as porosity. Fracture and cleat properties, i.e. density, length, area, aperture and porosity, were inputs for permeability calculation using fracture permeability published equations. Also, a multilinear regression (MLR) model was built for permeability estimation by utilizing the burial depth and properties of fractures and cleats. The coal seam obtained modelled permeability is a continuous curve capturing vertical heterogeneity in both qualitative and quantitative ways. The MLR model improved the match compared to the published permeability equations. Results show that the modelled MLR permeability perfectly matches the actual diagnostic fracture-injection/falloff test (DFIT) and wireline formation tester mini-DST permeabilities. The study showed the role of petrophysical logging in evaluating coal permeability by minimizing the uncertainty associated with the traditional permeability estimation. The technique provides denser permeability points for the static model, significantly enhancing the model properties distribution. It is important to mention the benefit of this technique in selecting the best reservoir portion of the target seam during lateral wells planning.

In order to obtain a reliable production forecast for the coal seam gas wells, a history matching was usually conducted to calibrate the simulated water and gas rates to the observed values. This p...

This paper takes a new approach to the modelling and visualisation of sequestered CO $$_2$$ in subsurface reservoirs and its migration pathways. We model the gas as discretised packets moving along paths within a graph or network. The movement of the packets will be governed by chip-firing. This new approach provides a new insight into the modelling of CO $$_2$$ migration in porous media with complex geological architectures. We compare and contrast this new graph theoretic approach with traditional methods and demonstrate that similar results are obtained, with the added advantage that the new methods are quick to implement and execute. In addition, the new methods are more flexible and can more accurately capture the variation in the stratification of the encasing rock.

Fluvial sediments with multi-scale channels are difficult to model using classical two-point statistical methods, e.g. sequential indicator simulation (SIS) or object-based modelling (ObjM). Multiple-point statistics (MPS) has been used to generate facies, fracture and porosity distributions based on pattern statistics derived from training datasets. However, the ability of these three methods to reproduce channel geometry and continuity is not clear, especially when using differently spaced conditional data. This paper presents a case study to compare the application of these three methods in reproducing channels from a section of Amazon River based on two differently spaced conditional data sets. Results show that: the reproduction accuracy is similar between MPS and SIS; MPS provides the most connected channel facies (or most channel continuity) as compared to SIS and ObjM; and using a hand-drawn facies based on the sampling points yield a similar accuracy to that achieved by using the reality facies distribution as the training image. Finally, we conclude that the application of MPS does not significantly increase the reproduction accuracy when compared to SIS channel models; however, MPS can generate realistic models with respect to channel geometry and continuity.

The Precipice Sandstone is traditionally interpreted as a braided fluvial deposit that transitions upwards into meandering channel deposits responding to a rise in base level that eventually deposi...

The Lower Jurassic (Sinemurian to Pliensbachian) Precipice Sandstone is the oldest formation and a regional aquifer in the Surat Basin, straddling southeast Queensland and northern New South Wales....

Differential compaction plays a key role in influencing the palaeogeographic organisation of many depositional systems. In the Jurassic Walloon Subgroup, Surat Basin, Eastern Australia, the process of compensational stacking contributes significantly to the complex coal layer architecture and is documented in mine exposure, borehole and seismic datasets. Despite this understanding, current best-practices do not formally consider the mechanics of compensational stacking when populating palaeogeography facies in coal seam gas (CSG) reservoir models. To address this limitation, a hybrid modelling workflow was developed in which numerical rules representing the process of differential compaction are used explicitly to condition an iterative workflow containing traditional geostatistical facies modelling algorithms. The workflow is facilitated by a newly developed open source plugin which allows grid decompaction in Schlumberger PETREL™ 2015. Application of the workflow was tested in a CSG production area containing closely spaced wellbores and a 3D seismic survey. In this area, facies models were constructed using both traditional geostatistical approaches and the newly developed hybrid methodology. Comparison of these models suggests that facies models constructed via unconstrained geostatistical approaches often result in unrepresentative realisations, inconsistent with coal seam architectures as observed in seismic and outcrop. The hybrid geostatistical-forward modelling approach developed during this study was better able to reproduce complex alluvial stacking patterns, particularly with respect to coal seam amalgamation, bifurcation and washout.

Understanding the controls on coal seam distribution and geometry is fundamental for planning coal seam gas production. In the Jurassic Surat Basin of South East Queensland, Australia, the spatial continuity of coal seams in the Walloon Coal Measures is highly variable and often difficult to map and predict, even with closely spaced (

A surrogate model approximates a computationally expensive solver. Polynomial Chaos is a method used to construct surrogate models by summing combinations of carefully chosen polynomials. The polynomials are chosen to respect the probability distributions of the uncertain input variables (parameters); this allows for both uncertainty quantification and global sensitivity analysis. In this paper we apply these techniques to a commercial solver for the estimation of peak gas rate and cumulative gas extraction from a coal seam gas well. The polynomial expansion is shown to honour the underlying geophysics with low error when compared to a much more complex and computationally slower commercial solver. We make use of advanced numerical integration techniques to achieve this accuracy using relatively small amounts of training data.

Water blocking damage, caused by the invasion of external fluids into the coal seams during hydraulic fracturing, is one of the reasons causing coalbed methane wells uneconomic in most areas of China. This paper presents an experimental study of water blocking damage on coal based on the measurements of surface tension, contact angle, gas-phase permeabilities and adsorption and desorption of nitrogen on synthetic coal samples. Distilled water, KCl, AN, and KCl+AN solutions were used as testing liquids in this study. Results show that the hydraulic fracturing fluid with surfactant AN causes the lowest damage to the reservoir permeability; the surfactant AN reduces the surface tension of the liquid and increases the wettability of liquid to coal reservoir; and the surfactant AN inhibits the occurrence of capillary and Jamin effects efficiently. It is concluded that the surfactant AN can reduce the water blocking damage rates of coal reservoirs; and the hydraulic fracturing fluid mixed with 1.5% KCl and 0.05% AN reduces the effect of water blocking damage on the coal permeability.

A reservoir in the upper Miocene Huangliu formation from the Dongfang (DF) area of Yinggehai Basin is characterized by overpressure and hydrothermal fluids with CO2 accumulations. The shallow-marine gravity-flow deposits of the Huangliu formation provide an opportunity to study the impact factors on reservoir quality under overpressure and a CO2-rich environment. The current study examined the impact of sandbody types, diagenetic alteration, high-overpressure and CO2 accumulations on reservoir quality by comparing between the DF-A (CO2-rich) and DF-B (CO2-poor) areas. The channel sandbody, sheet sandbody and neritic sandbar are recognized from the Huangliu formation in the study area. The sandbody type is the most important factor for controlling reservoir quality. The bottom current reworked channel (BCRC) and reworked sheet sandstones of gas layer #I in the DF-B area have the best reservoir properties. This is due to winnowing away the original (very) fine component (such as mud) by bottom current, resulting in a slight increase of grain size and marked increase of pore-throat radius and permeability. Mechanical compaction and cementation are the main diagenetic factors for reducing primary porosity. High-overpressure can protect the primary porosity to some extent by resisting the compaction effect. The intrusion of late CO2-rich hydrothermal fluids affects mesodiagenesis in two ways. On the one hand, it can cause intense dissolution of detrital minerals and early calcite cements, resulting in a higher proportion of secondary porosity in the CO2-rich DF-A area than in the CO2-poor DF-B area. On the other hand, it can result in precipitation of cements, such as siderite and ankerite, through CO2-water-rock reactions. Overall, CO2 accumulations has an insignificant contribution on the increase of porosity. Intense dissolution by CO2 accumulations can increase the connectivity of pores and permeability, whereas precipitation of minerals leads to decreased permeability.

This paper investigated the impact of geological and engineering factors on coal seam gas production in horizontal wells. The results were then used to compare the performance of proxy models based on linear and quadratic response surfaces and Universal Kriging (UK) to models based on Polynomial Chaos Expansion (PCE). A simple reservoir model was created using a commercial reservoir modelling software package which includes the capability to construct proxy models. The simple model was used for the dynamic modelling of cumulative gas production and peak gas rate under uncertainty in the input variables, e.g. the reservoir principal permeability and permeability in orthogonal directions varied as ratios of the principal permeability, porosity, gas content, coal saturation and the angle between the horizontal well and the principal permeability direction. The simulation results for cumulative gas production and peak gas rate were used to generate training data for proxy models, which were then used to predict the simulated output for other combinations of input parameters. Error analysis was conducted for each proxy model and used to compare and contrast the different modelling techniques. In addition, we investigated the sensitivity of the model to changes in the input variables. The results indicate that, for the given study, proxy models based on linear regression were not good estimators for cumulative gas production and peak gas rate. However, when enough training points were utilized, all other techniques provided good estimates. The best performing proxy model was a cubic PCE. In addition, the cubic PCE proxy model provided direct access to the sensitivity of the gas production to changes in the values of the input variables. Considering the main effects, the changes in the principle permeability and the porosity were predominant factors for the cumulative gas production and peak gas rate, respectively. As for the pairwise interactions, the combined effect of the principle permeability and the coal saturation had the most impact on the cumulative gas production, followed by the combined effect of the drilling angle and the ratio of the permeabilities in the y-direction and the x-direction, indicating that gas production can be improved by optimizing the orientation of the horizontal well. In addition, the combined effect of the coal saturation and the porosity had the most impact on the peak gas rate, an interesting result that warrants further investigation in future studies.

This paper presents an uncertainty analysis of coalbed methane resources estimation for a coal seam gas field containing multiple coal seams. Firstly, logs from nine wells and laboratory data from nine coal seams were used to predict the coal thickness, ash content and gas content at nine boreholes. Secondly, the structural models were determined using the well correlation, structural contour and coal seam thicknesses maps from coal mine data by the convergent gridder and sequential Gaussian simulation methods. Then, distributions of coal density and ash content were generated in 3D by using sequential Gaussian simulation based on the well log interpretations. Then, the distributions of gas content for each cell were built by two methods; one is multivariable regression analysis in 3D and the other is sequential Gaussian simulation based on the log interpreted gas content. Finally, coalbed methane resources were estimated based on the cell volume, coal density, net to gross ratio and gas content. In coalbed methane resources estimation, four different density cutoffs were used to define the net to gross ratio of coal in 3D. Results show that the gas contents decreases with increase in depth though with increases of vitrinite reflectance ratio, fixed carbon content and pressure. Calculated gas content from linear multivariate regression by using parameters of ash content, volatile matter content and fixed carbon content and sample's burial depth matches well with laboratory measured values. The total coalbed methane resources estimated are similar by the two geological modelling processes, the multivariable regression analysis in 3D and the sequential Gaussian simulation. It has been found that the effects of coal density cutoffs on coalbed methane resources for different coal seams are different.

Igneous intrusions in or adjacent to coal seams impact the coal quality directly and cause hazards for both coal mining and coal seam gas extraction. Specifically, sills can be identified at borehole level by wireline logs, e.g. natural gamma-ray, density, and resistivity tools because of their unique petrophysical characteristics. The literature describes also the use of surface seismic surveys as a tool for mapping thick sills. However, there is no precise and efficient way to delineate its horizontal distribution where sills are thin in thickness, e.g. less than 5 m. This paper presents an integrated method to predict igneous sill distribution in the Rangal Coal Measures, which are the Late Permian seams from the Blackwater Group in the Bowen Basin, based on petrophysical logs and seismic attributes. In this study, the mean amplitude, half-energy time, and root mean square amplitude from a post-stack 3D seismic survey have been used and compared. Results show that the sill thickness ranges from 0.5 m to 6.4 m with an average of 2.1 m from the analysed 12 wells; The prediction results of the sill are depending on the time-depth windows for calculating and mapping the half-energy time and their cut-offs; The half-energy time calculated with a time-depth window of about 40 ms with a cut-off of 13.5% yields the highest prediction accuracy of 83%. Compared to the mean amplitude and root mean square, the half-energy time is found the best surface seismic attribute in predicting horizontal sill distribution. The sequential Gaussian simulation is successfully used in mapping the sill distribution for the whole study area.

The Permian coal-bearing strata in the Sunan Syncline block contains abundant coalbed methane (CBM) resources. However, systematic studies of CBM geological characteristics in the block are still lacking which severely hinders the CBM development. This paper presents a synthetic study of the CBM geological characteristics in the block from the aspects of gas accumulation conditions and geological controls. Results show that the coal seams are dominated by medium-to high-volatile bituminous coals with the coal structure of normal and cataclastic, possessing relatively high fracability and permeability. The total thickness and gas content of the main coal seams are 9–12 m and 2–21 m3/t, respectively. The CBM in the shallow and deep parts of the block shows the feature of secondary bacterial gas and thermogenic gas, respectively. The roof lithologies of the coal seams and the structure types in the block provide good gas sealing conditions for CBM. In addition, the groundwater migration from the flanks to the axial region of the Sunan Syncline leads to relatively high gas content in the deep part of the block. Based on the CBM geological characteristics, the CBM exploration potential in the block was evaluated, and 2 zones were selected as favorable targets for CBM exploration.

The combination of Stratigraphic Forward Modelling and geostatistical technique can be used to improve the quality and comprehensiveness of the sedimentary reservoir model then reduce the costly data collection procedures to understand the reservoirs. The Stratigraphic forward modelling (SFM) is a process-based method comprising s realistic complexities and heterogeneities of its subsurface sedimentary architecture and may be applied in generating an enhanced model where limited well and seismic data available. The proposed method in this study is to generate a large SFM-basin scale then identify a field-scale location within this and applying some relevant transformation factor that matches the field conceptual deposition. Grainsize distributions may be inferred from well logs and compared against the grain size model in the SFM. Set of differences or residuals can be analyzed spatially and modeled using geostatistical techniques. Adding the modeled residuals to the SFM grain size will ensure that the hard data is honored. It is expected that more reasonable and defendable model characterization can be generated along with the main co-existed uncertainties and risks that can be captured and analyzed. The proposed methodology will incorporate the best advantage of each technique: process-based method for geological realism and Geostatistic methods for data conditioning.

Spatial coalbed methane (CBM) resource estimation is based on spatial distributions of coal, coal adsorbed gas content and coal density. However, the spatial distribution of gas content can be generated via two different geological modeling processes: (1) The gas content distribution is generated by geological modeling based on the interpreted gas content at boreholes; (2) distributions of gas content related logs or coal properties are generated firstly, then the gas content distribution is calculated based on the spatial distributions of logs or coal properties by the relationship between the gas content and logs or coal properties. This paper presents a study to compare the impact of these two processes on CBM resource estimation for coal seam no. 3 (CS-3) in southeast Qinshui Basin, China. Well logs from 22 wells, laboratory data from five wells and well tops from 131 wells for CS-3 are used in log interpretation and geological modeling. The simple kriging (SK) is used to build the structural model and the coal distribution. Weighted and unweighted omni-directional variograms for structural residual and coal thickness are calculated using an in-house program. Logs of gamma-ray (GR) and density (DEN or RHOB) are distributed in 3D by using sequential Gaussian simulation (SGS) with SK algorithm. Artificial neural network (ANN) is used to build the relationship of the measured raw gas content (RGC; gas content in raw coal basis) with the logs of GR, DEN and measured depth (MD). Then the RGC is distributed in 3D by the two geological modeling processes. CBM resources are calculated in 3D based on the cells' volume, coal density and RGC. Results show that RGC increases with an increase in burial depth. Total CBM resources for the study area calculated by these two processes are similar for CS-3 but the distribution probability of high gas content is highly different which is important for locating wells.

Hydraulic fracturing is applied to stimulate low permeability coals by producing a conductive fracture that enhances the connectivity between a wellbore and coal reservoir. The extant literature suggests that hydraulic fractures (HFs) can be vertical or horizontal, and may sometimes extend to neighbouring aquifers. This paper presents a quantitative study, using numerical simulations with a compositional simulator, into the effect of HF direction and its connectivity with aquifer on coalbed methane (CBM) production. Results show that vertical HFs yield higher peak gas rates than horizontal HFs, assuming that the permeability and volume of HF zones are the same. The extension of a HF into an aquifer results in high water production; however, the cumulative gas production is similar to models where the HF is constrained in a coalbed and the volume of the aquifer is less than 1.79 × 106 m3. An increase in aquifer volume causes decreases in gas production, but increases in water production, in fact, the peak gas rate and cumulative gas production decreases logarithmically with the increase in aquifer volume. When HFs extend into aquifers, with a volume of at least 34.8 × 106 m3, both peak gas rates and cumulative gas production yields decrease, and there is 10 times more cumulative water production than is seen in models without HFs. The results of the numerical simulations used in the study are justified by the production performance of a well from a producing CBM field.

Geological storage of CO2 is considered widely as an efficient method of mitigation of greenhouse gas emission. CO2 storage mechanism includes structural trapping, residual gas trapping, solubility trapping and mineral trapping. The shale cap rock acts as a seal for the storage when CO2 accumulates at the top of the reservoir. The injected CO2 may migrate through the cap rock under buoyancy force or pressure build-up which depends on the seal capacity of the cap rock. As a result, the effectiveness of containment of injected CO2 in the reservoir is largely dependent on the migration rate of CO2 through the cap rock. This paper investigates the effects of CO2 leakage through cap rock by a combination of experimental studies and numerical simulation. Firstly, experimental measurements on shale core samples collected from Australian cap rocks were conducted to determine properties, such as capillary pressure, pore size distribution and permeability. Based on the measured cap rock properties, the effect of thickness and permeability of cap rocks on CO2 leakage was studied using a commercial compositional simulator. Experimental results show that the permeabilities of the shale samples measured by transient pulse technique range from 60 to 300 nD; a non-Darcy calibration factor which equals the ratio of the measured permeability divided by 1000, is identified for samples with permeability lower than 1000 nD. Numerical simulation results show that the largest leakage of CO2 through the seal (cap cock) is about 7.0% with seal thickness of 3m and vertical permeability of 90 nD; both shale thickness and permeability affect the CO2 leakage significantly; with a given seal permeability, the leakage rate has a power relationship with shale thickness.

This paper presents a sensitivity analysis in permeability estimation by interpreting injection-falloff test and logging data for a producing coalbed methane field in Southeast Qinshui Basin. Injection-falloff test data are interpreted by an infinitely acting, constant compressibility and radial homogeneous model. Log interpretation is based on the Archie equation using data of shallow laterolog resistivity. The cementation factor of coal is calculated using laboratory measurements. Based on the interpreted cementation factors and the assumed fracture geometries, the sensitivity in permeability estimation using logging data is analyzed. Results show that the permeabilities are 0.041, 0.012 and 0.035 mD for coal seam #3 in wells #W-1, W-5 and W-6, respectively, from the interpretation of injection-falloff test data; the calculated coal cementation factors range widely from 0.9 to 1.8 with average of 1.3. In order to match the log interpretation results with those from injection-falloff tests, different fracture spacing is used in log interpretation for the three wells. The fracture spacing varies from 0.39 to 0.67 mm, and the average fracture aperture varies from 0.229 to 0.398 μm for the three wells. The cementation factor has the highest impact on estimation of permeability if the cementation factor, mud filtrate resistivity and fracture spacing are varied with 10% from the base case. Effect of fracture aperture’s heterogeneity on permeability is depending on the standard deviation and average of fracture aperture. Effective permeability has a stronger relationship with geometric mean of face and butt cleats aperture than with total porosity for different face and butt spacing models.

The coalbed methane (CBM) resources of China are located mainly in 9 basins, Ordos, Qinshui, Jungar, Diandongqianxi, Erlian, Tuha, Tarim, Tianshan and Hailaer. Qinshui Basin, one of the richest CBM basins in China, has boosted its annual CBM production to 3×109 m3 (106 Bcf). The coal seams in Qinshui Basin are significant with high gas content but strong heterogeneous permeabilities ranging from 0.1 to 10 mD. This paper investigates the effects of spatial distribution characteristics of coal permeability on CBM production. The study area is the South Shizhuang CBM district, Southeast of Qinshui Basin. The distributions of porosity, ash content, coal density and gas content of the coal seam are generated using sequential Gaussian simulation (SGS) with only one realisation because this paper only justifies the effects of coal permeability on CBM production. The permeabilities of 17 wells are determined by matching these wells' water and gas production with bottom-hole pressure as constraint. Then, the distributions of coal permeabilities are generated using SGS with a commercial simulator. The history matched permeabilities range from 1.5 to 12 mD with average of 2.9 mD of the 17 wells. Eight variogram models are used to build the distributions of permeability. The cumulative gas productions of two different well-spacing cases, 300 m and 2000 m, are compared. There are 20 realisations of permeability for each of the eight models. The results show that historical matching can be used to obtain the porosity multipliers and the permeabilities in wells. The major direction of variogram has less effect on the uncertainty of field CBM production than variogram range. The effects of variogram range on the uncertainty of CBM production are positive for the case with short well spacing and vice versa for the case with long well spacing.

This paper presents a study on predicting coalbed methane (CBM) production based on reservoir properties. Two hundred numerical models with different reservoir properties which are generated by a Monte Carlo method are numerically simulated using a compositional simulator. Empirical equations are built to estimate the gas recovery, peak gas rate, time to peak gas rate and gas production decline rates by analysing the relationships between reservoir properties and gas production rates. The peak gas rate, time to peak gas rate and gas production decline rates are used in the rate–time fit equation to predict the gas production rate. Results show that the combination of the modified Morse potential energy equation and the exponential decline equation can be used to fit the gas production for the entire production period of CBM wells. The regression coefficients between the calculated and numerical simulated gas recovery, logarithmic peak gas rate and logarithmic time to peak gas rate are 0.82, 0.86 and 0.80,...

Drilling horizontal wells in low permeability coal seams is a key technology to increase the drainage area of a well, and hence, decrease costs. It’s unavoidable that some parts of the horizontal section will be drilled outside the targeted coal seam due to unforeseen subsurface conditions, such as sub-seismic faulting, seam rolls, basic geosteering tools, drilling practices and limited experiences. Therefore, understanding the impact of horizontal in-seam drilling performance on coal seam gas (CSG) production and remaining gas distribution is an important consideration in drilling and field development plans. This study presents a new workflow to investigate the impact of horizontal in-seam performance on CSG production and gas distribution for coal seams with different porosity, permeability, permeability anisotropy, initial gas content (GC), initial gas saturation and the ratio of in-coal length to in-seam length (RIIL). First, a box model with an area of 2 km × 0.3 km × 6 m was used for conceptual simulations. Reduction indexes of the cumulative gas production at the end of 10 years of simulations were compared. Then, a current Chevron well consisting of a vertical well and two lateral wells, was selected as a case study in which the impact of outside coal drilling on history matching and remaining gas distribution were analysed. Results show that the RIIL plays an increasing role for cases with decreasing permeability or initial gas saturation, while it plays a very similar role for cases with varied porosity, permeability anisotropy and GC. The size and location of outside coal drilling will affect the CSG production and remaining gas distribution.

This paper presents a study on the characteristics of graphite-like crystallites (GCs) in coals with different maximum vitrinite reflectance (Ro,max) which can be used to describe the rank of coal. Laser Raman spectroscopy (LRS), X-ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM) were used in testing 17 coal samples with different ranks. Results show that the GCs in coal undertook through three consecutive processes including aromatisation, condensation and polymerisation. Five coalification upgrading yield to six stages that are corresponding to six different ranges of Ro,max. With the increasing coal rank, the GCs grow larger with improving quality and eventually evolve into graphite crystals. HRTEM observation also reveals that GCs in coal have undergone a graphitization process with increases in percentage, size, and order. [Received: April 13, 2017; Accepted: November 28, 2017]

This paper presents a geo-engineering and economic analysis of the potential for enhanced coalbed methane (ECBM) recovery and CO2 storage in the South Shizhuang CBM Field, Southeast Qinshui Basin, China. We construct a static model using the well log and laboratory data and then upscale this model to use in dynamic simulations. We history match field water and gas rates using the dynamic model. The parameters varied during the history match include porosity and permeability. Using the history matched dynamic model, we make predictions of CBM and ECBM recoveries for various field developments. We build a techno-economic model that calculates the incremental nominal net present value (NPV) of the ECBM incremental recovery and CO2 storage over the CBM recovery. We analyse how the NPV is affected by well spacing, CH4 price, carbon credit and the type of coal. Our analyses suggest that 300 m is the optimum well spacing for the study area under the current CH4 price in China and with a zero carbon credit. Using this well spacing, we predict the recoveries for different injection gas compositions of CO2 and N2 and different injection starting times. The results show that gas injection yields incremental CBM production whatever the composition of the injected gas. Pure CO2 injection yields highest ECBM for low swelling coals while flue gas injection gives highest ECBM for high swelling coals. However, the differences in recoveries are small. Injection can be economically viable depending on the CH4 price and the carbon credit. At current prices and no carbon credit, flue gas injection is commercial. At higher CH4 prices and/or with the introduction of carbon credits, co-optimisation could be commercially viable. High carbon credits favour injecting pure CO2 rather than other gases because this stores more CO2. Injecting CO2 at late stage increases CO2 storage but decreases the project's NPV. High-swelling coals require about $20/tonnes additional carbon credit.

Enhanced coalbed methane (ECBM) core flooding experiments are a direct way to observe the gas displacement process, the competitive adsorption and the effect of coal swelling and shrinkage on coal permeability. This study reports two ECBM experiments. In the first experiment, pure N2 is injected (N2-ECBM) to a coal sample saturated with CH4 while, in the second experiment, pure CO2 is injected (CO2-ECBM) to the same coal sample cleaned and resaturated with CH4. We record the volumes and composition of the effluent gas with respect to time. Then the gas rate and gas composition are history matched using a commercial reservoir simulator. The results show that the breakthrough of N2 occurs earlier than CO2 breakthrough (after approximately 0.1 day of injection compared to 0.43 day). The recovery factor of CH4 is 71% for the N2-ECBM and 86% for the CO2-ECBM at a 10%-molar percentage of CH4 in the produced gas stream. The N2 injection causes moderate increases in coal permeability whereas the injection of CO2 reduces coal permeability significantly. The maximum strain of CO2 injection is higher at the initial stage of CO2 injection but decreases after several days of injection. The extended Langmuir adsorption model predicts the compositional adsorption amounts of N2 and CH4 better for the N2-ECBM than for the CO2-ECBM. A co-optimisation concept is presented to analyse the coupling of ECBM with CO2 storage which shows that early times CO2 storage efficiency is higher than CH4 recovery efficiency. Later CO2 storage efficiency decreases due to CO2 production and CH4 recovery dominates the co-optimisation.

This paper presents an experimental and modelling study of the adsorption/desorption of pure gases CH4, CO2 and N2 and their binary and ternary mixtures on coal samples obtained from southeast Qinshui Basin, China. Results show that the adsorbed amounts of N2, CH4 and CO2 have approximate ratios of 1.0:1.3:2.4, respectively. No significant hysteresis from adsorption to desorption is observed for pure N2 and CH4 whereas significant hysteresis is measured for CO2 in CO2-CH4 and CO2-CH4-N2 mixtures and CH4 in the N2- CH4 mixture. The experimental observations are modelled using three different models, namely the extended Langmuir (EL), the Langmuir-based ideal adsorbed solution (L-IAS) and the Dubinlin-Radushkevich-based ideal adsorbed solution (D-R-IAS). The models predict well the experimental observations for desorption tests. But the measurements for the low adsorbate capacity in binary and ternary mixtures are overestimated by the prediction models. It is found that the EL model predicts the CO2-CH4 desorption test better while the D-R-IAS model is the best model for the CO2-CH4-N2 adsorption.

This paper presents a numerical simulation study that demonstrates history matching and production prediction for an actual horizontal coalbed methane (CBM) well located in Australia. A brief analysis of limited core analysis and well log data is presented. Numerical reservoir simulation is used to carry out a manual history matching to the field data of gas and water production rates and well bottomhole pressure. The matching parameters are porosity, relative permeability and skin factor. The reported field data show that there are sharp changes in the well bottomhole pressure and water and gas rates. This response of the reservoir is matched with a numerical model that has a varying skin factor along the horizontal well. This is deemed reasonable given that the drilling fluid has longer contact with the formation at the heel of the well, causing more formation damage. But the field data indicates that the formation damage is mitigated quickly with production. This is explained by the fact that the invaded mud is forced back during water and gas production and coal shrinkage. The production predictions show that skin factor and coal shrinkage have important effects on the CBM production of a horizontal well. However, the coal formation damage controls the gas rate more than the shrinkage for the examined case study with the assumed coal shrinkage parameters.

This paper presents a stochastic analysis of coalbed methane (CBM) resources for a coal seam in southeast Qinshui Basin, China. Log and laboratory data are used to predict the coal thickness, coal ash content and coal gas content. Using reservoir modelling, the distributions of the karst collapse column (KCC), coal seam thickness, coal quality and coal gas content are generated. The convergent interpolation and sequential Gaussian simulation methods are used to model the surface and structure of the coal seam. The structural models are determined by the surface structure and coal seam thickness. Based on the structural models, the coal and KCC are converted to two facies and their distributions are obtained using object modelling. The coal density distributions are simulated based on each facies model using the sequential Gaussian simulation. Finally, different realisations are used to study CBM resources. The results show that the heterogeneities in coal seam thickness and coal quality lead to significant uncertainty in estimating CBM resources. A model with lower heterogeneity gives a greater CBM resource. The distributions of KCC, coal seam thickness, coal quality and gas content are the main sources for uncertainty in CBM resource estimation. The density variogram and top structure contribute less to the uncertainty in CBM resources.

Matrix compressibility, shrinkage and swelling can cause profound changes in porosity and permeability of coalbed during gas sorption and desorption. These factors affect the distribution of pressure, methane production and CO2 sequestration. This paper compares the effects of cleat compression and matrix shrinkage and swelling models with the injection of different compositional gas mixtures (CO2 and N2). It shows that well performance, pressure distribution and properties of the seam are strongly affected by matrix shrinkage and swelling. Matrix shrinkage and swelling also affects net present value of the enhanced coalbed methane recovery scheme. In order to select the best enhanced coalbed methane recovery schemes, economic evaluation and sensitivity studies are necessary.

This paper presents an integrated approach of discrete fracture network modelling for a naturally fractured buried-hill carbonate reservoir in the Jingbei Oilfield by using a 3D seismic survey, conventional well logs, and core data. The ant tracking attribute, extracted from 3D seismic data, is used to detect the faults and large-scale fractures. Fracture density and dip angle are evaluated by observing drilling cores of seven wells. The fracture density distribution in spatiality was predicted in four steps; firstly, the ant tracking attribute was extracted as a geophysical log; then an artificial neural network model was built by relating the fracture density with logs, e.g., acoustic, gamma ray, compensated neutron, density, and ant tracking; then 3D distribution models of acoustic, gamma ray, compensated neutron and density were generated by using a Gaussian random function simulation; and, finally, the fracture density distribution in 3D was predicted by using the generated artificial neural network model. Then, different methods were used to build the discrete fracture network model for different types of fractures of which large-scale fractures were modelled deterministically and small-scale fractures were modelled stochastically. The results show that the workflow presented in this study is effective for building discrete fracture network models for naturally fractured reservoirs.

Following two decades of intensive exploration, coal seam gas (CSG) production in the Surat Basin has begun to dramatically increase to meet the capacity of three newly completed CSG to liquefied natural gas (LNG) export projects. As the industry’s focus shifts from appraisal to exploitation, the production forecasts underpinning these LNG projects are being tested. In some cases predicted reservoir performance is found to be invalidated by observed production data, a condition that may require costly amendments to project schedule and scope. The deviation between actual and predicted reservoir performance can often be attributed to an incomplete understanding of parametric uncertainties present in static or dynamic reservoir models. To address this limitation, this study aims to explore the parametric controls upon CSG production behaviours with a series of simulation experiments. Distributions of reservoir parameters were compiled from 152 open-source well completion reports available in three areas along the eastern edge of the Surat Basin. These distributions were validated and then sampled to extract representative ranges for subsurface factors including gas content, permeability, net coal thickness, Langmuir pressure, Langmuir volume and drainage area. These inputs were used to construct single well radial models, which were then simulated to generate predictions of monthly and cumulative produced fluid volumes. The results of this study indicate that net coal thickness and lateral coal connectivity are the most sensitive factors with respect to cumulative gas production, while permeability was the single most influential parameter affecting the rate of gas production.

Laterally discontinuous coal measures are common in alluvial settings due to interaction with fluvial systems. Under these conditions it is difficult to accurately represent coalbeds and interburden sandstone bodies in static and dynamic models at a regional scale. These challenges are compounded in the Walloon Coal Measures by non-uniform drill spacing, which varies from clustered to sparse and insufficient outcrop exposures available to constrain the correlations. To address these issues, this study investigates a nested approach to facies modelling of the Upper Juandah Member of the Jurassic Walloon Coal Measures in the Surat Basin, Queensland, which contains some 3,600 wells, of which half were analysed for lithofacies distributions. This approach contrasts the application of truncated Gaussian simulation, object modelling and multiple-point geostatistical simulation. First, a regional scale structural model was developed based on the correlation of sub units within the basin and the lithofacies were then interpreted from normalised wireline logs. Then geometries of individual facies were defined from two local scale models (~6 × 6 km2) where dense drilling, 3D seismic and paleocurrent analysis data were available to constrain the models. Three training images, generated by object modelling, an analogue of one part of the Ob River, and an interactive method were subsequently used to model primary channels, channels and crevasse splays, respectively. Truncated Gaussian simulation was used in modelling the distribution of marginal and coal swamp. The final model is a combination of the model with primary channels and channels, and the model with marginal and coal swamp. This approach is the first trial in modelling swamp and channel distributions at a regional scale by integrating data from local models, depositional analogues and paleo-flow interpretation in the Surat Basin.

Abstract This paper integrated Flow Zone (FZ), single sandstone sequence, with the study of fracture, and gave a fine characterization and modeling of fractured low permeability reservoir. It pointed out that calculating the porosity and permeability for low permeability reservoir based on FZ and building the 3D discrete fracture network (DFN) distribution model integrated with the static fracture character and the density distribution of high angle fracture (HAF) and low angle fracture (LAF) are efficient methods for fractured low permeability reservoir. This brings forward the use of FZ and considerable sequence stratigraphy controlled modeling method, and brings forward to build fracture surface from point which controlled by the density distribution of HAF and LAF. The result shows the efficiency of a modeling approach for a fractured low permeability reservoir by integrating low permeability characterization and fracture study. Introduction It is still a challenge to model fractured low permeability reservoirs, such as characterizing the low permeability matrix, 3D fracture distribution, fracture character, fracture and matrix coupling character. 1–5 From the onset of development of Baobei Block, Baolong oilfield in 1994, the detailed sand architecture, flow zone and possible reservoir performance were known. Based on reservoir performance from exploitation, the low productivity could not be characterized by flow zone only and hence the need for an integrated characterization and modeling of the low permeability matrix and fracture is very important. This paper is based on detailed core analysis, characterization of low permeability matrix, and model build up of the low permeability matrix controlled by multi-surface and flow zone, and construction of 3D discrete fracture network (DFN) distribution model integrated with the 2D fracture distribution, predicted by well-log response and structural curvature, and the fracture occurrence.

It is important to predict the economical feasibility of geological sequestration of CO2. This paper applies reservoir simulation to model the characteristics of CO2 injection in the specific injection site location.It could provide input to the economic evaluations by defining Bottom Hole Pressure and injection relationships. Selecting an appropriate grid system was particularly discussed in this study. The flexible corner point grid system and grid refinement technology were proven to be suitable for the simulation of CO2 geological sequestration. By this approach, we finally obtained the ultimate capacity of reservoir to store CO2, and further produced data about different possible injection scenarios needed for economic modeling. It was concluded that the geological structure and direction of CO2 migration were two important factors in the selection of the optimum well pattern. The results showed that using one well can satisfy the injection requirement, and also CO2 geological sequestration in the Barrow Sub-basin is feasible.