The current presentation date and time shown is a TENTATIVE schedule. The final/confirmed presentation schedule will be notified/available middle of October 2019. If we have learned anything from the North American experience, unconventional resources cannot be exploited by small incremental projects. If we are to be successful in developing these types of reservoirs, we have to make project scale operations work to bring these resources to market in a timely manner. A number of Eastern Hemisphere unconventional gas projects have raised interest, neared completion or are commencing deliveries.
Case studies can be instructive in the evaluation of other coalbed methane (CBM) development opportunities. The San Juan basin, located in New Mexico and Colorado in the southwestern U.S. (Figure 1), is the most prolific CBM basin in the world. It produces more than 2.5 Bscf/D from coals of the Cretaceous Fruitland formation, which is estimated to contain 43 to 49 Tscf of CBM in place. For a long time, the Fruitland formation coals were recognized only as a source of gas for adjacent sandstones. In the 1970s, after years of encountering gas kicks in these coals, operators recognized that the coal seams themselves were capable of commercial gas rates. CBM development benefited greatly from drilling and log data compiled from previous wells targeting the deeper sandstones and an extensive pipeline infrastructure that was built to transport conventional gas. These components, along with a U.S. federal tax credit and the development of new technologies such as openhole-cavity completions, fueled a drilling boom that resulted in more than 3,000 producing CBM wells by the end of 1992. The thickest Fruitland coals occur in a northwest/southeast trending belt located in the northeastern third of the basin. Total coal thickness in this belt locally exceeds 100 ft and individual coal seams can be more than 30 ft thick. The coals originated in peat swamps located landward (southwest) of northwest/southeast trending shoreline sandstones of the underlying Pictured Cliffs formation. The location of the thickest coals (Figure 1) coincides with the occurrence of overpressuring, high gas content, high coal rank, and high permeabilities in the San Juan fairway ("fairway"). The overpressuring is artesian in origin and is caused by water recharge of the coals through outcrops along the northern margin of the basin. This generates high vertical pressure gradients, ranging from 0.44 to 0.63 psi/ft, which allow a large amount of gas to be sorbed to the coal. Coal gas in the San Juan basin can contain up to 9.4% CO2 and 13.5% C2 . Chemical analyses suggest that thermogenic gases have been augmented by migrated thermogenic and secondary biogenic gas sources, resulting in gas contents ranging up to 700 ft 3 /ton. Coal rank in the fairway ranges from medium- to low-volatile bituminous and roughly coincides with those portions of the basin that were most deeply buried. Coals in the fairway typically have low ash and high vitrinite contents, resulting in large gas storage capacities and excellent permeabilities of 10 md from well-developed cleat systems.
A useful first step in the characterization of any new coal area is to compare its characteristics with those of successful CBM projects. Table 2 summarizes the characteristics of several successful projects in the US and includes parameters related to reservoir properties, gas production, gas resources, and economics. The table shows that successful projects have many similarities, including high permeabilities and high gas resource concentration; however, the table does not include aspects such as government incentives or high-value markets, which could elevate a marginal project to commercial status.
Hafez, Hafez (ADNOC) | Al Mansoori, Yousof (ADNOC) | Bahamaish, Jamal (ADNOC) | Saputelli, Luigi (Frontender) | Escorcia, Alvaro (Frontender) | Sousa, Sergio (Halliburton) | Rodriguez, Jose (Halliburton) | Mijares, Gerardo (Halliburton)
Identifying opportunities in the installed capacity and proactively mitigating the limiting factors are paramount objectives for pursuing profitable production assurance. Although integrated asset modeling has been the de facto technology for supporting production planning and optimization work processes, its application is not fully adopted as it presents challenges when attempted to be used in a large-scale of multiple oil and gas assets.
This paper describes ADNOC’s innovative approach to develop a large scale subsurface to surface integrated asset modeling (LSSSIAM) solution by focusing on the desired business outcome. The paper introduces a new concept of right complexity modeling (RCM) to drive the type and level of complexity of the model/simulation based on the desired business outcome and other factors that influence the quality of the decision-making process.
The methodology has been applied on a large-scale of multiple assets for effective production assurance that integrates the subsurface to the surface physical phenomena as required by the desired business outcome—the technical assurance of production plans within the context of a country. For the presented example, the proposed methodology resulted in the design of a solution where the subsurface phenomena are represented with a data-driven model to specifically address the requirements of the decision-making process which the solution supports.
This resulted in the development of a first-of-its-kind countrywide production model that rigorously considers the properties and physics from the wells to the point of supply while also considering the subsurface phenomena as related to the production potential of the reservoirs and wells.
The solution leverages the rigor of first-principle reservoir models to obtain a data-driven proxy model suitable for integration with a first-principle model covering more than 7,000 wells, multiple network and asset facilities, and a supply point transfer countrywide network. The solution can run in a matter of seconds, allowing for the optimization of a desired objective function or the effective analysis of operational scenarios, which can include short- and mid-term production assurance, opportunities identification to increase production to capture value opportunities from a country-wide production capacity context, and compensating for possible shortfalls resulting from unplanned operational disturbances in other assets.
Rock stiffness is important in design as it affects the stresses and deformation around openings. Many rocks are anisotropic and those of sedimentary origin are frequently highly nonlinearly elastic. Traditionally elastic properties are inadequately measured using uniaxial test methods. This paper examines the results of uniaxial, triaxial and hydrostatic testing for the elastic behaviour of rock based on the assumption of orthotropic behaviour. The effects of fluid pressure on effective stress are also discussed. The mathematics are presented for each case. The testing methods involve step-wise loading of triaxial or hydrostatic samples that are fitted with strain gauges. The effects of fluids on deformation are determined by gas injection. The simple hydrostatic test process enables rock fragments to be tested to determine their anisotropy. This however requires an estimation of at least one of the values of Poisson’s ratio.
Rocks are complex composites of different minerals. As a consequence their mechanical properties are highly variable. This variability extends through varying elastic to post elastic behaviour. For a general elastic solid there are six stresses and six engineering strains which are linked by either a compliance (Equation 1) or stiffness matrix, each with 36 terms. Because of the symmetry of these matrixes the number of terms may be reduced to 21. Practically this is still a very large number of parameters to determine from a physical test on a piece of rock, particularly as this piece of rock is frequently a cylindrical core or more conveniently a fragment.
The general formulation of Equation 1 means that quite complex effects can be accounted for. For example a normal stress to a plane may cause a shear strain in that same plane. More realistically shear stress acting on a plane may lead to strain (dilation or compaction) perpendicular to the plane.
If we make the convenient, but not necessarily correct, approximation that the rock behaves in an orthotropic manner, then the number of independent terms in the compliance matrix drops from 21 to nine (allowing for symmetry) as shown in Equation 2. Three of these are shear terms that are difficult to measure directly, but may be estimated. The orthotropic approach does however mean that the options such as dilation or compaction perpendicular to the plane on which shearing acts are assumed to be zero.
Bedded coal and iron ore deposits in Australia are usually hosted in complexly jointed, faulted or folded, highly anisotropic rock masses. In coal, these often comprise moderately strong siltstones and sandstones with weak coal seams, siltstones and shales. For iron ore, these comprise strong banded iron formations discretely interbedded with very weak shales. Slope failure mechanisms typically involve sliding along bedding (anisotropy) planes combined with joints or faults acting as release planes or forming step-path failure mechanisms.
Slope stability modelling techniques have evolved over the years and increased in complexity with continuous improvements in computing capability and available software. Less than 20 years ago, basic kinematic analysis was the primary means of designing large rock slopes. In the 2000s, the use of two-dimensional limit equilibrium analysis and numerical modelling rapidly increased with faster computing. As we approach the 2020s, three-dimensional limit equilibrium and finite element analysis software are readily available and offer a range of options to model the behavior of complex, anisotropic rock masses. The results obtained by these different modelling approaches, for example, isotropic vs. anisotropic, or 2D vs. 3D can vary significantly depending on the geological conditions.
This paper presents case studies from both open pit iron ore and coal mines that compare the factor of safety (FoS) obtained from 2D and 3D limit equilibrium modelling approaches. The case studies clearly show the limitations of 2D modelling when the rock mass being excavated is highly anisotropic in nature and when large-scale geological structures are present whose geometry cannot be adequately represented in plane strain. Results further indicate that modelling solely in 2D can lead to either the over-estimation or under-estimation of FoS, by failing to locate the section of slope with the lowest FoS or failing to adequately model the anisotropic conditions under which failure is likely to occur. The tools are now readily available to facilitate 3D modelling techniques alongside existing 2D techniques to complete a comprehensive review of slope stability. This will allow both the optimization of slope designs to be completed, and increase design reliability by identifying the sections of slope more susceptible to failure in true 3D space.
In 2014-15, income from sales and services from coal and iron ore mines in Australia was approximately $115 Billion (AUD), which accounted for approximately 80% of total mining and quarrying sector (ABS, 2016).
The Pilbara Region of Western Australia hosts the majority of economically extractable iron ore deposits in Australia. Hundreds of open cut mines are operated by major mining companies near the townships of Newman, Paraburdoo and Tom Price with single operations often having access to several individual pits in similar ground conditions. Due to the broad regional expanse of the operations, particularly in the iron ore sector, a very high extraction rate is achieved despite vertical development rates remaining relatively low (typically one to three benches or 10m to 30m per year in a single iron ore pit). Final pit depths or total rock slope heights range from less than 100m to 350m.
The Hunter Valley Region of New South Wales and the Bowen Basin Region in Queensland host the main coal deposits used for energy and steel manufacturing. Mining typically begins with an initial excavation, called a box cut, and then progresses down dip in a series of strips, with the coal closest to the surface extracted first. Pit geometry is dictated by equipment capabilities, the location of economic coal seams, and geotechnical constraints to achieve an acceptable design. Individual bench heights typically do not exceed 60m and overall excavated slope heights rarely exceed 150m.
A full-field dynamic simulation model has traditionally been seen as the benchmark for assimilating all available static and dynamic data to develop robust production forecasts. Santos’ experience modelling the Walloon Coal Measures in its Surat Basin acreage has shown that the performance of individual wells producing from this CSG reservoir is governed by reservoir variability at a fine-scale. This presents a fundamental challenge in developing full-field dynamic models that can accurately describe and predict production performance down to the scale of individual coal seams.
Current Queensland CSG projects have focussed on the most prospective acreage, however as subsequent developments move to more marginal areas a greater understanding of the subsurface will be required for optimum development. The target formations will increase in geological complexity, such as Santos’ Surat Basin acreage on the edge of the CSG fairway. Here wells produce from a greater number of distinct coal reservoir units, and how these reservoir units are structured and relate to each other governs reservoir connectivity and defines long-term production performance. Each reservoir unit is comprised of multiple coal plies, all with their own unique maceral distribution and cleating characteristics. These fine-scale properties define the reservoir's dynamic behaviour, and can be impossible to upscale such that these characteristics are preserved at a coarse scale. Consequently, accurately modelling individual well performance will require a fine-scale model to capture and characterise this variability.
In development areas where the quantity and quality of reservoir data gathered from exploration and appraisal is sparsely populated, these fine-scale models will need to be populated geostatistically. Without model-scale appropriate control data from production and pressure measurement in the development wells to provide constraints however, a probabilistic model will not accurately define fine-scale behaviour of specific reservoir units. These data requirements can help shape the appraisal scope for new areas and define an appropriate level of surveillance for producing assets.
Traditional full-field dynamic modelling has fundamental limitations for interrogating complex unconventional CSG reservoirs at a fine scale. Because of this, alternative workflows are required to answer the subsurface questions necessary to develop CSG assets such as the Surat Basin effectively. This paper details a selection of workflows explored to address this pragmatically, as well as their limitations and associated data requirements. This will also assist in identifying data gaps needed for optimum reservoir management and to aid in the development of these challenging CSG reservoirs.
The Australia Pacific LNG (APLNG) Downstream Project comprised construction of a two-train LNG plant, two 160,000 m3 LNG storage tanks, a LNG loading jetty, and associated infrastructure on Curtis Island, near Gladstone, Queensland. The facility utilises ConocoPhillips’ proprietary Optimized Cascade ® process to liquefy natural gas. Project planning began in 2008 and construction commenced in 2011. LNG production from Train 1 began in December 2015 and Train 2 came on line in October 2016. In August 2017, the final 90-day two-train lenders test was successfully concluded and included an operational component in which the LNG Facility operated at ten per cent above nameplate capacity for the 90-day period. This successful outcome was achieved through collaboration, integration and robust execution plans by the APLNG Operations, APLNG Project, ConocoPhillips LNG Technology and Licensing and Commissioning and Start-up work teams. In an effective strategy to support the drive to APLNG first cargo, the combined teams formed a fully Integrated Completions Team in 2015. This team worked together enabling rapid development of the operations workforce capability and resulted in both trains achieving performance tests at first attempt.
The APLNG Project operability assurance and operations readiness program commenced with a collaborative workshop, attended by Operations, Projects and Commissioning and Start-up representatives. A focus on high collaboration and integration between the teams backed by ConocoPhillips’ Operability Assurance (OA) and Operations Readiness (OR) principles identified 370 critical business deliverables. Learnings were leveraged from across ConocoPhillips assets (including Darwin LNG) as they pertained to readiness best practice. APLNG Readiness Assurance guidance was established to create specific functional readiness trackers to measure every action supporting the 370 deliverables. A simple and effective tool was developed and supported by robust monthly review forums where each action was tracked and rolled up to S-Curves. These deliverables translated to over 7,000 unique line items tracked over the entirety of the readiness implementation. This work was leveraged by the Integrated Completions Team which implemented robust lessons learned from Train 1 to realize immediate results, delivering a 33% reduction in the Train 2 start-up schedule.
The combined efforts of the teams delivered two highly operational trains within the 2016 calendar year resulting in the production of additional cargoes. The successful execution and implementation of OA/OR principles combined with strong integration of APLNG Operations into the APLNG Project phase laid the foundation for exceptional first year operational and production performance. This meant the APLNG Operations Team moved from a newly formed team to a high functioning and critically evolving team in support of the APLNG Downstream LNG Facility.
A system for reducing solids production in Surat basin coal seam gas (CSG) wells was developed in the laboratory and tested in the laboratory and field trials.
Several thousand CSG wells were completed in Surat basin in eastern Australia using what was considered an economic method at a time - an open hole with a predrilled liner.
Although the majority of the wells are meeting production expectations, a many wells are producing a substantial amount of solids originating from an interburden rock representing approximately 90% of completed interval length and comprising mudstones, sandstones, and siltstones rich in illite/smectite and other water-sensitive clays. Relatively fresh water, with total dissolved solids (TDS) of approximately 4000 to 7000 mg/l, produced from multiple thin coal seams during dewatering and production phases is causing the interburden rock to swell or disintegrate. Prolific wells with high water rates or high gas velocity are capable of carrying solids to the surface where the solids are deposited in separators, flowlines, and water-treatment settling ponds. Higher solids concentration on lower-rate wells are causing issues with positive cavity pumps (PCP), the artificial lift method of choice in CSG wells. Pump intake plugging with solids, excessive torque and rotation seizure, and wear of tubing/rod strings are frequent causes of workovers and shorter-than-expected pump run-life. Some wells are able to flow freely; however, an extra monitoring program is required to ensure wellheads are not suffering from solids-induced erosion.
Recompletion of the wells is not considered practical at this stage because pre-perforated joints form an integral part of the 5 ½-in. or 7-in. casing string, which is cemented above the Walloons subgroup coal seams. An external casing packer (ECP) is often used. Some coal seams were underreamed, thus further complicating recompletion. Plugging existing wells and drilling a pair of wells using same surface location and infrastructure have been considered.
A chemical wellbore stabilization solution been developed to alleviate/stop solids production from the interburden rock. The treatment comprises two fluids separated by a spacer that contains clay stabilizer that is typically 3 to 7% KCl, the same as drilling mud base. Proprietary surfactant reduces the possibility of coal damage. Regained permeability testing performed using crushed and sieved coal pack plugs indicated a low level of damage. The wellbore stabilization system could be energized/foamed to reduce hydrostatic pressure and increase compressibility, hence increasing the chance of contacting rock surface in an enlarged wellbore.
The key objective of multiple Coal Bed Methane (CBM) development operations is to determine cost effective methods to allow sustainable economic production and maximum reserves recovery. The cost of workovers as well as the associated deferred production may overwhelm the economic viability of the field. The primary reason for workovers is progressive cavity pump (PCP) system failures. Here, we demonstrate the use of a machine learning framework that can be used to customise each workover configuration such that it optimises PCP run-life, respecting the well's heterogeneity and age. The framework can be generalised into three major parts: 1) converting the dynamic production data into a stationary surrogate model for the well; 2) the use of Gaussian process regression to create a function that estimates runlife; 3) an optimiser that will search the functional space to recommend the best completion design. A telemetry and completion dataset for PCP run-lives from years 2014-2018 was obtained across the Surat and Bowen basins. After filtering data for completeness, 1499 PCPs remained in the cohort, of which, 895 failed during the observation period. A small portion of the original data was used as a test set. Our work suggests that PCP run-life can be extended by taking a multivariate statistical approach to provide recommendations for customised completions and production strings per well that respect the wells' geology and production history and thereby improve life of field economics.