Unlocking Ensemble History Matching Potential with Parallelism and Careful Data Management

Improvements in reservoir simulation computational time thanks to GPU-based simulators and the increasing computational power of modern HPC systems, are paving the way for a massive employment of Ensemble History Matching (EHM) techniques which are intrinsically parallel. Here we present the results of a comparative study between a newly developed EHM tool that aims at leveraging the GPU parallelism, and a commercial third-party EHM software as a benchmark. Both are tested on a real case. The reservoir chosen for the comparison has a production history of 3 years with 15 wells between oil producers, and water and gas injectors. The EHM algorithm used is the Ensemble Smoother with Multiple Data Assimilations (ESMDA) and both tools have access to the same computational resources. The EHM problem was stated in the same way for both tools. The objective function considers well oil productions, water cuts, bottom-hole pressures, and gas-oil-ratios. Porosity and horizontal permeability are used as 3D grid parameters in the update algorithm, along with nine scalar parameters for anisotropy ratios, Corey exponents, and fault transmissibility multipliers. Both the presented tool and the benchmark obtained a satisfactory history match quality. The benchmark tool took around 11.2 hours to complete, while the proposed tool took only 1.5 hours. The two tools performed similar updates on the scalar parameters with only minor discrepancies. Updates on the 3D grid properties instead show significant local differences. The updated ensemble for the benchmark reached extreme values for porosity and permeability which are also distributed in a heterogeneous way. These distributions are quite unlikely in some model regions given the initial geological characterization of the reservoir. The updated ensemble for the presented tool did not reach extreme values in neither porosity nor permeability. The resulting property distributions are not so far off from the ones of the initial ensemble, therefore we can conclude that we were able to successfully update the ensemble while persevering the geological characterization of the reservoir. Analysis suggests that this discrepancy is due to the different way by which our EHM code consider inactive cells in the grid update calculations compared to the benchmark highlighting the fact that statistics including inactive cells should be carefully managed to correctly preserve the geological distribution represented in the initial ensemble. The presented EHM tool was developed from scratch to be fully parallel and to leverage on the abundantly available computational resources. Moreover, the ESMDA implementation was tweaked to improve the reservoir update by carefully managing inactive cells. A comparison against a benchmark showed that the proposed EHM tool achieved similar history match quality while improving the computation time and the geological realism of the updated ensemble.

ANALISIS PERBANDINGAN DAYA DUKUNG DAN PENURUNAN FONDASI BORED PILE MENGGUNAKAN METODE TEORITIS, METODE ELEMEN HINGGA DENGAN UJI TEST PDA (PILE DRIVING ANALYZER) (STUDI KASUS PEMBANGUNAN GEDUNG B RUMAH SAKIT MUHAMMADIYAH METRO)

Pada umumnya perencanaan suatu bangunan meliputi perencanaan bangunan atas (upper structure) dan perencanaan bangunan bawah (sub structure). Fondasi merupakan bagian bangunan bawah (sub structure) yang berhubungan langsung dengan tanah mempunyai peranan penting memikul seluruh beban bangunan lain di atasnya, maka dari itu perlu dilakukan perhitungan daya dukung serta penurunan yang akan terjadi di dalam perencanaan desain dan juga pengujian setelah pelaksanaan pekerjaan fondasi. Pada pembangunan gedung B RSU Muhammadiyah menggunakan tipe fondasi bored pile. Ditinjau dari penyelidikan jenis tanah, beban struktur, lingkungan sekitar proyek, dan pengujian lapangan dengan test PDA (Pile Driving Analyzer) dan CAPWAP maka tujuan dari penelitian ini adalah untuk menghitung daya dukung dan penurunan fondasi bored pile dengan cara static (menggunakan prinsip-prinsip mekanika tanah) menggunakan metode teoritis, metode elemen hingga, dan cara (dinamic) menggunakan metode experimental dengan uji lapangan test PDA (Pile Driving Analyzer) dan CAPWAP serta dapat menginterpetasikan hasil data PDA (Pile Driving Analyzer) dan CAPWAP. Berdasarkan hasil dari penelitian dapat disimpulkan bahwa dalam perhitungan daya dukung hasil perbandingan selisih terkecil pengujian static menggunakan metode L. Decourt terhadap hasil pengujian dinamic hasil CAPWAP pada kedua titik uji dengan nilai 4,06% pada titik BH-01 dan -9,29% pada BH-02 dan hasil selisih terkecil pada metode elemen hingga dengan hasil CAPWAP ada pada titik BH-01 yaitu -9,8%. Hasil selisih perbandingan terkecil penurunan adalah menggunakan metode Paulus&Davis terhadap hasil CAPWAP pada BH-01 yaitu -13% dan BH-02 yaitu -23%. Hasil PDA Test pada tiang No.1 terjadi overstressed karena nilai CSX lebih tinggi dari tegangan ijin tekan, untuk EMX tiang No.2 melebihi efisiensi hammer yang disarankan, pada laporan hasil CAPWAP tidak terdapat keterangan dari CAPWAP match quality dan terdapat data yang belum lengkap diberikan dalam laporan, seperti persentase kerusakan fondasi (BTA) dan tinggi jatuh hammer test (STK).

Compressed Dimension of Reservoir Models Uncertainty Parameters for Optimized Model Calibration and History Matching Process

The algorithms and workflows have been developed to couple efficient model parameterization with stochastic, global optimization using a Multi-Objective Genetic Algorithm (MOGA) for global history matching, and coupled with an advanced workflow for streamline sensitivity-based inversion for fine-tuning. During parameterization the low-rank subsets of most influencing reservoir parameters are identified and propagated to MOGA to perform the field-level history match. Data misfits between the field historical data and simulation data are calculated with multiple realizations of reservoir models that quantify and capture reservoir uncertainty. Each generation of the optimization algorithms reduces the data misfit relative to the previous iteration. This iterative process continues until a satisfactory field-level history match is reached or there are no further improvements. The fine-tuning process of well-connectivity calibration is then performed with a streamlined sensitivity-based inversion algorithm to locally update the model to reduce well-level mismatch. In this study, an application of the proposed algorithms and workflow is demonstrated for model calibration and history matching. The synthetic reservoir model used in this study is discretized into millions of grid cells with hundreds of producer and injector wells. It is designed to generate several decades of production and injection history to evaluate and demonstrate the workflow. In field-level history matching, reservoir rock properties (e.g., permeability, fault transmissibility, etc.) are parameterized to conduct the global match of pressure and production rates. Grid Connectivity Transform (GCT) was used and assessed to parameterize the reservoir properties. In addition, the convergence rate and history match quality of MOGA was assessed during the field (global) history matching. Also, the effectiveness of the streamline-based inversion was evaluated by quantifying the additional improvement in history matching quality per well. The developed parametrization and optimization algorithms and workflows revealed the unique features of each of the algorithms for model calibration and history matching. This integrated workflow has successfully defined and carried uncertainty throughout the history matching process. Following the successful field-level history match, the well-level history matching was conducted using streamline sensitivity-based inversion, which further improved the history match quality and conditioned the model to historical production and injection data. In general, the workflow results in enhanced history match quality in a shorter turnaround time. The geological realism of the model is retained for robust prediction and development planning.

CEO tenure and firm value

Our study is the first to provide systematic evidence of a hump-shaped CEO tenure-firm value relation. Cross-sectionally, firm value starts to decline after fewer years of CEO tenure in more dynamic industries, if CEOs are less adaptable to changes, and in the presence of lower labor market frictions. Overall, the dynamics of CEO-firm match quality appear to be a first-order driver of the CEO tenure-firm value association, as explained by CEO characteristics (adaptability), firm/industry characteristics (dynamism), and labor market characteristics that facilitate optimal matching between firms and CEOs.

The role of Accurate Self-Assessments in Optimising Mate Choice

Individuals are thought to seek the best possible romantic partner in exchange for their own desirability. We investigated the strategies that individuals use when choosing a partner, and whether these strategies optimise the quality of mutually interested partners (‘matches’). Further, we investigated whether these matching outcomes were affected by the accuracy of one’s self-perceived mate value. Participants (1501 total) took part in a speed dating experiment whereby they rated themselves and others on attractiveness variables and indicated their willingness to date each opposite sex partner they interacted with. We then calculated participants’ selectivity, minimum and maximum standards, accuracy, match quality, and match quantity. Individuals were somewhat accurate in their self-evaluations, and these self-evaluations guided individual’s minimum and maximum quality standards for a potential partner, leading to higher quality matches. These findings extend social exchange models by emphasising the adaptiveness of accurate self-evaluations in mating contexts.

Integrated Modelling and Performance Reviews Helps to Unlock New Opportunities in a 40-year-old Mature Field Under Waterflood

Field X is one of largest oil fields in Brunei producing since 1970's. The field consists of a large faulted anticlinal structure of shallow marine Miocene sediments. The field has over 500 compartments and is produced under waterflood since 1980's through 400+ conduits over 50 platforms. A comprehensive review of water injection performance was attempted in 2019 to assess remaining oil and identify infill opportunities. Large uncertainties in reservoir properties, connectivity and fluid contacts required that data across multiple disciplines is integrated to identify new opportunities. It was recognized early on that integrated analysis of surveillance data and production history over 40 years will be critical for understanding field performance. Hence, reviews were first initiated using sand maps and analytical techniques. Tracer surveys, reservoir pressures, salinity measurements, Production Logging Tool (PLT) were all analyzed to understand waterflood progression and to define connectivity scenarios. A complete review of well logs, core data from over 30 wells and outcrop studies was carried out as part of modelling workflow. This understanding was used to construct a new facies-based static model. In parallel, key dynamic inputs like PVT analysis reports and special core analysis studies were analyzed to update dynamic modelling components. Prior to initiating the full field model history matching, a comprehensive impact analysis of the key dynamic uncertainties i.e., Production allocation, connectivity and varying aquifer strength etc. were conducted. An Assisted History Matching (AHM) workflow was attempted, which helped in identifying high impacting inputs which could be varied for history matching. Adjoint techniques were also used to identify other plausible geological scenarios. The integrated review helped in identifying over 50 new opportunities which potentially can increase recovery by over 10%. The new static model identified upsides in Stock Tank Oil Initially in Place (STOIIP) which if realized could further increase ultimate recoverable. The use of AHM assisted in reducing iterations and achieve multiple history matched models, which can be used to quantify forecast uncertainty. The new opportunities have helped to revitalize the mature field and has potential to almost increase the production by over 50%. A dedicated team is now maturing these opportunities. The robust methodology of integrating surveillance data with simulation modelling as described in this paper is generic and could be useful in current day brown field development practices to serve as an effective and economic manner for sustaining oil production and maximizing ultimate recovery. It is essential that all surveillance and production history data are well analyzed together prior to attempting any detailed modelling exercise. New models should then be constructed which confirm to the surveillance information and capture reservoir uncertainties. In large oil fields with long production history with allocation uncertainties, it is always a challenge for a quantitative assessment of History match quality and infill well Ultimate Recovery (UR) estimations. Hence a composite History Match Quality Indicator (HMQI) was designed with an appropriate weightage of rate, cumulative & reservoir pressure mismatch, water breakthrough timing delays. Then HMQI parameter spatial variation maps were made for different zones over the entire field for understanding and appropriately discounting each infill well oil recovery. Also, it is critical that facies variation is properly captured in models to better understand waterfront movements and locate remaining oil. Dynamic modelling of mature field with long production history can be quite challenging on its own and it is imperative that new numerical techniques are used to increase efficiency.