Prediksi Tekanan Pori Berdasarkan Data Logging Sumur Menggunakan Deep Neural Network

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Meredita Susanty

Abstract

Tekanan pori formasi merupakan data penting yang digunakan dalam mendesain parameter dalam operasi pengeboran. Kesalahan dalam menentukan tekanan pori formasi dapat menimbulkan permasalahan dalam pengeboran yang dapat menyebabkan bertambahnya biaya pengeboran hingga kehilangan nyawa pekerja. Tekanan pori bisa didapatkan melalui pengukuran langsung maupun menggunakan metode empiris. Pengukuran langsung tidak dilakukan di setiap kedalaman karena biayanya yang tinggi. Metode empiris memiliki keterbatasan dalam menentukan tekanan pori formasi dikarenakan metode ini memerlukan adanya keakuratan dalam analisis Normal Compaction Trendline dan batasan untuk digunakan pada formasi tertentu. Penelitian ini menggali potensi jaringan saraf tiruan untuk memprediksi tekanan pori berdasarkan data logging sumur. Dengan arsitektur jaringan saraf tiruan yang menggunakan tiga hidden layer, model dibangun dengan lima fungsi aktivasi dan metriks evaluasi Mean Absolute Error. Semua mampu memprediksi tekanan pori dengan baik yang ditunjukkan dengan nilai loss dibawah 0.5. Diantara kelima fungsi aktivasi, Exponential Linear Unit menghasilkan loss paling baik sebesar 0.07 dibanding model dengan fungsi aktivasi lainnya.

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How to Cite
Susanty, M. (2020). Prediksi Tekanan Pori Berdasarkan Data Logging Sumur Menggunakan Deep Neural Network. Petir: Jurnal Pengkajian Dan Penerapan Teknik Informatika, 14(1), 81 -89. https://doi.org/10.33322/petir.v14i1.964
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