Surat Basin

This paper assesses regulatory rules associated with drilling and completions activities in Queensland unconventional oil and gas plays. This assessment is based on a typology that classified rules into defined categories, defining their structure and what types of activities are required to assure them. This paper also reviewed a sample of ‘as built’ Well Completion Reports (WCR) to understand the self-assurance activities conducted by operating companies as well as to identify trends in compliance against a sample of rules.

The typology assessment identified that rulemaking was generally consistent across documents, and a clear balance existed between rules focused on design and rules focused on field operations. The assessment also identified the actual wording of rules could benefit by more standardisation in some areas. Importantly, this assessment also identified the large volume of complex assurance activities faced by inspectors.

The ‘as built’ data review identified a clear commitment to the written rules and evidence of self-assurance activities being consistently conducted by operators. This review also confirmed the value of WCR analysis and the potential to use them to measure compliance.

Whilst this paper has provided valuable insight into rule making and the approach to self-assurance taken by some operators, there are many areas of the wider regulatory system that would be well served by further analysis. This paper has proposed some recommendations for such analysis to help make a more holistic assessment of effectiveness in the future.

A novel, simple, economical, and time effective method to estimate the anisotropic permeability of the coals is presented in this paper. This method estimates the coal's anisotropic permeability by avoiding the tedious experimentation using triaxial permeameter or history matching exercises. This method calculates the absolute magnitude of the permeability of the sample. In this regard it is unlike other analytical permeability models, such as given by Palmer and Mansoori (1998) and Shi and Durucan (2014), that only calculate the permeability ratio (k/k0). The motivation is to find a method by which the permeability of the coal may be determined with reasonable accuracy by using only two easy measurements: 1) Mercury Intrusion Porosimetry (MIP) and; 2) Anisotropic stress-strain (σ-ε) measurement. The main blocks of the method are based on 1) cleat size which is obtained from MIP and randomly allocated to form flow-channels/cleats through the coal; 2) these cleats form parallel paths in the orthogonal face and butt cleat directions which provide the permeability; and 3) the cleat width (b) is stress dependent. This method is further validated by comparing with the experimentally measured stress-dependent permeability of Surat Basin (Australia) coal and a German coal in face cleat and butt cleat directions.

In coal seam gas (CSG) fields, where single wells tap multiple seams, it is likely that some of the individual seams hardly contribute to gas recovery. This study aims to examine the contribution of individual seams to the total gas and water production considering that each seam may have different properties and dimensions. A sensitivity analysis using reservoir simulation investigates the effects of individual seam properties on production profiles.

A radial model simulates the production of a single CSG well consisting of a stack of 2 seams with a range of properties for permeability, thickness, seam extent, initial reservoir pressure, compressibility and porosity. The stress-dependency of permeability obeys the Palmer and Mansoori (1998) model. A coefficient (α) relates seam radius, thickness, porosity, compressibility, permeability, and initial pressure. It is used to aid interpretation of the sensitivity study. Finally, a case study is modelled with 5 seams of different thicknesses and depths obtained from a producing well. The range in properties represents conditions found in the Walloon Coal Measures of the Surat Basin, relevant to the Australian CSG industry.

The sequence in which peak of gas production rate of each seam is achieved can be estimated using α. For α_top/α_bottom > 1, the bottom seam peaks first but achieves lower gas recovery than the top seam. For α_top/α_bottom < 1, the top seam experiences fast depletion and total gas production rates decrease drastically. The peak gas rate of each seam may be identified on gas production profiles depending on α. When 1 < α_top/α_bottom < 10, individual peaks merge. For 10 < α_top/α_bottom < 27, individual seams can be clearly identified as dual-peaks on production curves. For α_top/α_bottom > 27, the contrast between maximum rate and time to peak increases and the top seam’s contribution is significantly reduced in early production time. A more realistic case based on a section of an actual Surat Basin well with 5 seams confirmed that when the α_top/α_bottom of seams of greater permeability-thickness (kh) is higher than 27, gas recovery decreases. Even with higher total kh, seams with α ratio = 100 produced less gas than seams with α_top/α_bottom = 10. An increasing α ratio is associated with inhibition of less permeable seams and reduced overall well productivity.

There is an increasing need to understand the influence of faults in both gas production performance and the resulting potential impact on adjacent groundwater resources.Faults can exhibit a wide variety of hydraulic properties. Where resource development induces changes in pore pressure, the effective stress and thus the permeability can be transient. In this study, w explored strategies for characterizing fault zone properties for the initial purpose of evaluating gas production performance. The same fault characterization can then be incorporated into regional groundwater flow models to more accurately represent stress, strain and the resulting transmissivities when assessing the impact of gas development on adjacent aquifers.

Conventional fault zone analysis (juxtaposition, fault gouge or shale smear, fault reactivation) is combined with hydrodynamic analysis (distribution of hydraulic head and hydrochemistry) and surface water hydrology and hydrochemistry to evaluate across fault or up fault locations of enhanced hydraulic conductivity at specific locations of complex fault systems.

The locations of identified vertical hydraulic communication from the hydraulic analysis are compared with the fault zone architecture derived from the 3D seismic volume overlain with the in-situ stress characterization. This provides an independent method of assessing other potential hydraulic communication locations based on seismic alone where no other hydraulic or hydrochemical information is available. A groundwater model is used in an inverse approach to assess the hydraulic properties required to generate observed hydrochemical anomalies so that a realistic range of rock properties can be assigned throughout the geological model to other faults. We use a case study example of the Gloucester Basin in New South Wales in eastern Australia to demonstrate how some of these techniques can be applied. The Gloucester Basin has been subject to exploration of coal seam gas with some pilot testing but no commercial production. It also contains data from groundwater monitoring bores and surface water features. The methodologies described can be applied elsewhere when faults play a key role in determining gas production performance or characterisation of groundwater flow system hydraulics in gas development areas.

Production forecasting is required at all stages of coal seam gas (CSG) reservoir development. Depending on the stage of appraisal or development, different methodologies can provide the best fit for the forecasting objectives. This paper compares technical advantages and disadvantages of several forecasting approaches while considering potential accuracy, time required to construct the forecast and general fit for purpose. The basis of comparison is case studies of CSG projects in the Surat and Bowen basins.

In general, a very similar set of forecasting tools can be applied to CSG reservoirs as for the conventional oil and gas fields. A notable difference is gas desorption from the source rock, which needs to be included into numerical and analytical model and is typically described by adsorption isotherms. Some approaches, like Decline Curve and Pseudo Steady State Well Deliverability can be applied with minimal modifications. Flowing Material Balance and more detailed numerical reservoir simulations require changes to account for the gas desorption mechanism. However, these tools are already well established in the industry.

In addition to comparing the established approaches for CSG production forecasting, we propose a new hybrid method and compare its applicability to the other tools. The hybrid method uses output of the numerical reservoir simulation model and applies an analytical correction to adjust the predicted production rates to the actual observed data and to produce the forecast at possibly different bottom hole pressure compared to the original numerical model. The new hybrid method is recommended in cases where a quick forecast is required for fields with a large (hundreds and more) number of wells. The advantage of the new approach is that it provides a quick response while still maintaining the characteristics of the initial reservoir model.

Building on the successful results of the Surat Model presented by Zhang et al, SPE-186340-MS; this paper describes an amended methodology to simplify the distribution of coal bearing facies of the Walloon Coal Measures in the Surat Basin across a regionally significant Gas Project.

The workflow was created with the high vertical resolution to capture the detail of the coal horizons and decrease up-scaling and averaging artefacts in the 3D environment whilst honouring geological premise for fining-up sequences within stratigraphic units.

The model horizons were created using picks from six coal packages within the Juandah and Taroom Coal Measures. The coal seam packages divisions typically display a fining-up sequence with the top of the sequence most-often picked as coal. Unlike the initial workflow where a series of coal and sand sub-zones were picked in order to narrow statistical ranges to aid control of the lateral and vertical proportions within members. This workflow utilised a coal probability property to guide the spatial distribution of coals which resulted in a preserved statistical outcome from input log data to final modelled result that honoured well data whilst dramatically reducing dynamic run time. Coal distribution was modelled using the Truncated Gaussian Algorithm trended to this probability property. The non-coal proportion of the resulting property was populated with sands to create a final three facies property.

Net-to-gross was modelled as a separate property using moving average algorithm applied to up-scaled coal cells. This property was then multiplied against cell height filtering on coal cells from the facies modelling outcome in order to achieve a net coal outcome.

The use of a trend property to place coal within the model volume captures the natural fining-up sequences regionally through each stratigraphic unit without the need to tailor the depositional progressions using deterministic sub-horizon picks. As this property is dynamically updated with the introduction of new well data it removes the requirement for extensive manual statistical analysis.

A benefit of the use of a trending property is the honouring of regional variations in net coal and is defined by up-scaled well data. Importantly, the results yielded a seamless progression of coal thickness from areas of low data density to high data density.

This approach resulted in a highly detailed, geologically representative model that blends the requirements of delivering complexity of drainage architecture and a base case outcome.

The workflow presents an opportunity to model net coal regionally and locally within a single model with high resolution, honouring local data and regional distribution. This provides a model that characterises a credible geological outcome whilst representing a convincing dynamic simulation.

New models for particle embedment during micro-particle injection into naturally fractured reservoirs are developed. The proposed models aim to predict production benefit from the application of micro-particle injection during coal seam gas (CSG) stimulation with broader applications to other naturally fractured reservoirs. The elastoplastic finite element modelling is applied to coal sample from Surat basin (Australia), to predict micro-particle embedment and fracture deformation under various packing densities and closure stresses. The coupled lattice Boltzmann-discrete element model (LBM-DEM) is then used for permeability prediction. These results are combined in a radial Darcy flow analytical solution to predict the productivity index of CSG wells. Modelling results indicate that considering elastoplastic fracture surface deformation leads to smaller permeability increase and less production enhancement, if compared with the linear elastic deformation of fracture implemented in traditional models. Although focused on Australian coals, the developed workflow is more broadly applicable in other unconventional resources. Modelling of particle transport and leak-off in coal fracture intersected with a cleat using LBM-DEM approach demonstrates the effects of particle and cleat sizes, particle concentration and sedimentation on the leak-off process. The leak-off is significantly affected if the particle-cleat size ratio is higher than 0.5. Particle sedimentation increases leak-off into vertical cleat substantially, but has no effect on horizontal cleat. Suspensions of higher concentration result in higher leak-off for cleats with different apertures.

Electrofacies identification is a crucial procedure in reservoir characterization especially in the lack of lithofacies measurements from core analysis. Electrofacies classification is essential to improve permeability-porosity relationships in non-cored intervals. Flow Zone Indicator (FZI) is a conventional procedure for rock types classification whereas Clustering Analysis has been recently used as unsupervised machine learning technique to group a set of data objects into clusters with no predefined classes. In this paper, clustering analysis and flow zone indicator were adopted for the electrofacies characterization on a dataset obtained from incorporate of conventional core analysis and CPI logs (Effective Porosity, Water saturation and Shale volume) of three wells in the upper shale member/Zubair formation in Luhais oil field southern Iraq.

The FZI attains reservoir quality evaluation through hydraulic flow unit and kozeny-carman equation, which correlates between permeability, porosity, pore throat, pore geometry and tortuosity factor. The reservoir intervals of similar or convergent range of FZI values belong to a single hydraulic flow unit and reflect the geological attributes of texture and mineralogy therefore they represent specific rock type. In clustering analysis, two approaches were adopted for electrofacies identification: k-mean and Ward's Hierarchical clustering method. These three techniques were implemented by the use of R language, which is a powerful statistical programming tool. The prepared R codes in this research can be utilized in any reservoir characterization process to define the different electrofacies

The results of this research showed two implemented techniques have identified three key electrofacies with different levels of accuracy and approaches while four rock types have been predicted from the third technique. The k-mean clustering analysis was the most accurate method where each predicted electrofacies reflects the same vertical distribution of the lithofacies in the reservoir. On the other hand, the Ward's Hierarchical electrofacies prediction represents specific petrophysical properties with minor differences from real lithofacies distribution in the reservoir. Finally, electrofacies identification through the FZI technique has similar ranges of FZI values with specific porosity and permeability values. FZI technique showed difficulty in defining lithofacies boundaries within the reservoir and predicted four rock types.

Secondary oil recovery projects in naturally fractured carbonate reservoirs (NFR) often introduce uncertainties and challenges that are not common to conventional waterfloods. The recovery mechanism in NFRs relies on ability of the fracture network to deliver enough injected fluid to the matrix, as well as rate and magnitude of capillary interactions within the matrix rock, during which hydrocarbon displacement occurs. The imbibition measurements can be performed in the laboratory using core samples, but due to reservoir heterogeneity, certain limitations of the lab equipment and the quality of the core material, scalability of the core results to a reservoir model can be challenging.

This paper describes the design, execution and evaluation of the’ log-soak-log’ (LSL) pilot test conducted in a giant naturally fractured carbonate reservoir with a low-permeability matrix in Western Kazakhstan, where repeatable and reliable measurements of changes in water saturation were achieved across large intervals (tens of meters) using a time-lapse pulsed-neutron logging technique. Periodic measurements provided valuable observations of dynamic change in saturation and fluid level over time and allowed estimation of the rate and magnitude of imbibition in the slope margins, depositional settings and rock types of interest. Incorporation of the LSL results into reservoir models validated the ranges of water-oil relative permeability curves, residual oil saturation to water, irreducible water saturation, and capillary pressure assumptions. This validation constrained key subsurface uncertainty and updated the oil recovery forecast in several improved oil recovery (IOR) waterflood projects.