Carnarvon Basin

Africa (Sub-Sahara) Sahara Group discovered hydrocarbons in three wells drilled in Block OPL 274, located onshore in Nigeria's Edo State. Olugei-1 was drilled to a measured depth of 4537 m and encountered five hydrocarbon zones, with 33 m of net pay. Oki-Oziengbe South 4 was drilled to a measured depth of 3816 m and encountered 64.3 m of net pay in 13 hydrocarbon-bearing zones. Oki-Oziengbe South 5 was drilled to a measured depth of 3923 m and encountered 91 m of net pay in 19 reservoirs. Sahara Group (100%) is the operator. Asia Pacific Sino Gas & Energy Holdings (SGE) flowed gas (coalbed methane) from its first horizontal well in the Linxing production sharing contract (PSC) in China's Shanxi province.

Africa (Sub-Sahara) The drillship Ocean Rig Athena is preparing to drill appraisal and exploration wells offshore Senegal for a joint venture (JV) led by Cairn Energy. Two wells will appraise the SNE discovery, which was ranked by IHS CERA as the world's largest for oil last year. An exploration well will also be drilled in the Bellatrix prospect, for which mapping has indicated a potential 168 million bbl of oil resources. Cairn holds a 40% interest in the JV, with remaining interests held by ConocoPhillips (35%), FAR (15%), and Petrosen (10%). The Ksiri West-A exploration well drilled by Circle Oil on the Sebou permit onshore Morocco has flowed gas at a rate of 8 MMcf/D following tests. It is being readied for production.

Abstract

Compressional and shear traveltime logs (DTC and DTS, respectively) acquired using sonic logging tools are used to estimate connected porosity, bulk modulus, shear modulus, Young’s modulus, Poisson’s ratio, brittleness coefficient, and Biot’s constant for purposes of geomechanical characterization. We propose a data-driven technique to synthesize DTC and DTS logs in the absence of a sonic logging tool. Six shallow learning methods, namely ordinary least squares (OLS), partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), elastic-net regularization, multivariate adaptive regression splines (MARS) and artificial neural network (ANN), suitable for function approximation problems, are trained and tested to synthesize DTC and DTS logs. To that end, the six shallow learning models process 13 conventional and easy-to-acquire logs, namely lithology, gamma ray, caliper, density porosity, neutron porosity, photoelectric factor, bulk density, and resistivity at six depths of investigations. A total of 8,481 observations along a 4,240-ft depth interval in a shale reservoir were available for the proposed data-driven application. The ANN algorithm performs the best among the six algorithms. ANN-predicted DTC and DTS logs have coefficients of determination (R²) of 0.87 and 0.85, respectively, for Well 1. The next best prediction performance is provided by the MARS-predicted DTC and DTS logs, with accuracies of 0.85 and 0.83, respectively. PLS- and OLS-predicted DTC and DTS have accuracies measured by R² of 0.83 and 0.80, respectively, whereas the LASSO- and elastic-net-predicted DTC and DTS have accuracies of 0.79 and 0.75, respectively. The prediction performances of the six algorithms for DTC are always better than those for DTS. The ANN model trained in Well 1 is deployed in Well 2, which was drilled in the same reservoir. The ANN-predicted DTC and DTS logs in the 1,460-ft depth interval of Well 2 have R² of 0.85 and 0.84, respectively.

Commencement of initial field production is a unique opportunity to acquire reservoir surveillance information that can inform future reservoir performance. When a field is perturbed from original conditions with first production, there is potential for reservoir property uncertainty reduction by observing pressure measurements at non-producing wells with downhole pressure gauges and comparing the observed signal to a range of simulation model results.

The Wheatstone field, located offshore northwest Australia, has recently commenced production start-up to supply gas to the Wheatstone LNG facility. The operational guidelines required each development well to commence with a single well cleanup flow to the Wheatstone platform. The initial single well cleanup flows of the Wheatstone field allowed scope for the selection of a well flow sequence with observation at non-producing wells.

The recommended sequence of initial cleanup flows was designed with a focus on reducing reservoir uncertainties via the use of Ensemble Variance Analysis (EVA). EVA is a statistical correlation technique which compares the co-variance between two sets of output data with the same set of inputs. For the Wheatstone field well cleanup flow sequence selection, the EVA workflow compared the full field Design of Experiments (DoE) study of field depletion and a series of short early production reservoir simulation DoE studies of the gas field. The co-variance between the two DoE studies was evaluated. The objective of the EVA approach was to determine the startup sequence that would allow for the best opportunity for subsurface uncertainty reduction. This objective was met by ranking multiple cleanup flow sequence scenarios. The key factors considered for sequence selection ranking were the impact on business objectives such as future drilling campaign timing and location of infill wells, as well as insights on reservoir connectivity, gas initially in place and permeability.

The recommended sequence of well cleanup flows uses super-positioning of pressure signal to boost response at observation wells, which improves measurement resolvability. The selected sequence preserves key observation wells for each manifold and reservoir section for as long as possible before those wells were required to be flowed to meet operational requirements. Operational constraints and variations of the startup plan were considered as part of the evaluation.

A fault stability study constitutes a fundamental element of any subsurface injection project that involves faults within a storage complex, yet the transient geomechanical effects introduced due to CO₂-rock chemical interactions are rarely considered. This paper presents a review of the published work investigating the potential alteration of rock properties due to short to long term CO₂-host rock chemical interactions during commercial scale carbon capture and storage (CCS) operations. Furthermore, the authors of this paper are attempting to highlight the potential significance of these mechanical-chemical effect on the fault reactivation potential for a commercial scale carbon capture and storage (CCS) operation.

The reactive nature between CO₂ dissolved in formation water and the storage reservoir can significantly alter the hydraulic and mechanical properties of the host rock, which could in turn affect the storage potential of the target reservoir. Alteration of the host rock mineralogy due to chemical interactions with CO₂ have been well studied (Farquhar et al. 2015), but little is available in the published literature on the resulting changes in rock elastic properties (i.e. Young's modulus and Poisson's ratio) due to these reactions. Some recent experimental studies have suggested significant changes in rock properties occur. When we incorporated the geomechanical effects, induced by the rock elastic property changes documented in these published cases, into both 1D analytical and 3D numerical models based fault stability analyses for a Surat Basin reservoir, we observed significant modification of the reservoir storage capacity prior to reaching fault reactivation criteria.

Based on our review of the published literature and our fault stability analyses, we conclude that the chemical effects of CO₂ interaction with host rock needs to be experimentally tested to confirm if these effects are significant. If yes, then these effects should constitute an integral part of the geomechanical study for any large scale CO₂ injection exercise if there is a critically stressed fault as part of the storage complex.

Australia is uniquely positioned globally as a major energy provider, but this comes with multiple challenges that must be overcome to realize its full potential. LNG developments that are nearing fruition are set to make Australia the largest supplier of LNG in the world. The Asian LNG market continues to be the growth market. The development of the world's first coal bed methane (coal seam gas) to LNG projects on the east coast has created a robust east coast LNG export market, which in the near future is expected to coincide with domestic energy shortages arising from low exploration activity, maturing fields, higher costs, the interaction of government policy, commercial decisions and activism. As a result, unique approaches to project management and community relations have been developed that are complementary to the Australian consumer's needs for reliable, affordable and cleaner energy. The east coast demand for gas is likely to trigger new development of onshore Northern Territory gas in the short term, if political opposition can be managed. In Western Australia, new approaches leverage technologies such as floating LNG, and more utilization of existing infrastructure and plant capacity to achieve lower costs. This paper outlines Australia's natural gas supply & demand and the challenges to be faced in the coming years.

The crossplotting of elastic properties such as impedance, V_p/V_s ratio, density, Lambda-Rho and Mu-Rho has been used to characterize the fluid and lithology in seismic area. In general, 2D or 3D crossplot of the elastic properties was used because of a limitation of data visualization, and the best combination of the properties for the crossplot was selected subjectively or empirically, which can be biased depending on the interpreter's view. In this abstract, we propose a new workflow to overcome the limitations of the subjective selection of the axis parameters on the crossplots. We first apply non-linear transformation of the elastic properties from well logs, and select the best separable combination of the transformed properties. As the transformed elastic properties used for the combinations are high-dimensional (larger than 4D), it is not trivial to select the most separable properties visualizing them on the crossplots. Instead of the crossplotting, we use scatter-matrix-based-measure to quantify the separability of the combinations, and select the best combination with the largest separability. Finally, using multivariate probability density function (PDF) of the best combination from well logs and inverted elastic property volumes from seismic, we probabilistically analyze the facies on the seismic volume based on Bayesian inference. A field data has been used to demonstrate the effectiveness of our workflow.

Presentation Date: Tuesday, October 16, 2018

Start Time: 8:30:00 AM

Location: 209A (Anaheim Convention Center)

Presentation Type: Oral

Pore pressure prediction plays an important role in shale gas exploration and fracking technology. The pore pressure in shale cannot be directly measured but to be inferred by the normal compaction trend, so methods based on the effective stress theory are dedicated to establishing a function between seismic interval velocity and pressure. Among them the mostly used method is Eaton’s equation. However, how to precisely quantify the state of compaction remains unsolved. In this study, the AVO/AVA simultaneous inversion was introduced to estimate P-velocity. According to the exponential relationship between the pore pressure and the ratio of velocities, three different methods including the fitting method, the direct calculation method and the model-based direct calculation method based on the Eaton’s equation were used to estimate shale gas pore pressure, respectively. And then a comparative analysis was performed to see the impact of normal compaction trend on the result. It was found that the horizontal continuity of the model-based direct calculation method was the best. The result shows that the approach of estimating the normal compaction trend impacts the pore pressure significantly.

Presentation Date: Monday, October 15, 2018

Start Time: 1:50:00 PM

Location: 210A (Anaheim Convention Center)

Presentation Type: Oral

Summary In the past decades, many exploration wells have drilled into igneous rocks by accident because of their similar seismic expression to the common intended targets such as porous carbonate mounds, sheet sands or deepwater sand-prone sinuous channels. In cases where sedimentary features such as channels or fans cannot be clearly delineated, the interpretation may be driven primarily by bright spot anomalies, and a poor understanding of the wavelet polarity may compound this problem. While many wells that are drilled into igneous rocks were based on interpretation of 2D seismic data, misinterpretation still occurs today using high quality 3D seismic data. We propose an in-context interpretation workflow in which the interpreter looks for key clues or parameters above, below and around the target of interest to confirm the interpretation. Introduction Using modern 3D seismic surveys, significant work has been achieved over the past two decades in accurately imaging the geometry of igneous bodies (Hansen and Cartwright 2006; Holford et al., 2012; Jackson et al., 2013; Magee et al., 2014).

Summary Concepts for the relation between faults and folds in an extensional regime have revealed the importance of detailed mapping of fault zones, particularly in combined structural-stratigraphic traps. We show in a case study from the Australian North West Shelf that extensional fault zones are composed of several individual faults. Depending on the depth within the faulted interval, the individual faults may be interrupted by relay ramps. Additionally, release faults perpendicular to the main faults may introduce further potential breaches of the fault seal. Understanding the faults within the reservoir at this level of detail will assist in better understanding the fault seal risk for combined structural-stratigraphic traps.