JP2004538442A - Multivariate analysis by mass spectrometry - Google Patents

Abstract

The present invention produces high performance pavement asphalt based on the molecular composition of asphalt and raw crude oil or crude oil blend determined at least in part based on the relationship between high resolution mass spectrometry measurements and rheological properties. The selection of crude oil or crude oil blends.
[Selection diagram] Fig. 1

Description

【００２１】
式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１２０種の分子グループを用いて、性能を未知の原油スレートから得られる減圧残渣のＨＲ／ＭＳフィンガープリントを生成させる。
【００２２】
式Ｃ_ｎＨ_{（２ｎ±ｚ）}で示される２４種の炭化水素分子グループを評価する。分子グループのうち１７種（全体の７１％）は、アスファルトレオロジーランクの関数として強度差を呈する。グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトは、低芳香族性炭化水素分子グループ（ｚ≦８）に関し強度差を示さない。グループＩＶのアスファルトは一般に、グループＩ、ＩＩまたはＩＩＩのアスファルトよりも、芳香族性が中程度の炭化水素分子グループ（１０≦ｚ≦２６）に関しより小さい強度を呈する。グループＩＶアスファルトは一般に、グループＩ、ＩＩまたはＩＩＩのアスファルトよりも、高芳香族性炭化水素分子グループ（２８≦ｚ≦４４）に関しより大きい強度を呈する。
【００２３】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒが単一硫黄置換である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１９種の分子グループを評価する。分子グループのうち１０種（全体の５３％）は、４つのアスファルトグループ間で強度差を呈する。グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトは、低芳香族性硫黄分子グループ（ｚ≦１０）に関し強度差を呈しない。グループＩＩＩおよびグループＩＶのアスファルトは一般に、グループＩおよびグループＩＩのアスファルトよりも、芳香族性が中程度の硫黄分子グループ（１２≦ｚ≦２２）に関しより小さい強度を呈する。グループＩＶのアスファルトは一般に、グループＩ、ＩＩまたはＩＩＩのアスファルトよりも、高芳香族性硫黄分子グループ（２４≦ｚ≦３４）に関しより大きい強度を呈する。
【００２４】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルト、Ｒ＝Ｓ_２である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１０種の分子グループを評価する。１０種の分子グループのうち３種（全体の３０％）は、４つのアスファルトグループ間で強度差を呈する。データが大きな変動を呈することに注意しなければならない。一般に、グループＩＶのアスファルトは、グループＩ、ＩＩまたはＩＩＩのアスファルトよりも、高芳香族性Ｓ_２分子グループ（１４≦ｘ≦２０）に関しより大きい強度を呈する。
【００２５】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒが単原子酸素置換である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される２０種の分子グループを評価する。２０種の分子グループのうち１２種（全体の６０％）は、４つのアスファルトグループ間で強度差を呈する。ジスルフィド分子グループのときと同じように、酸素分子グループは、各アスファルトグループ内で強度に大きな変動を呈する。グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトは、低芳香族性酸素分子グループ（ｚ≦１０）に関し強度差を示さない。グループＩＶのアスファルトは、グループＩ、ＩＩおよびＩＩＩのアスファルトよりも、芳香族性が中程度の酸素分子グループ（１２≦ｚ≦２０）に関しより小さい強度を呈する。グループＩＩＩおよびＩＶのアスファルトは、グループＩまたはＩＩのアスファルトよりも、高芳香族性酸素分子グループ（２２≦ｚ≦３２）に関しより低い強度を呈する。ｚ＞３２である分子グループの場合、４つのアスファルトグループ間で強度差はない。
【００２６】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒ＝Ｏ_２である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１４種の分子グループを評価する。２０種の分子グループのうち１２種（８５．７％）は、４つのアスファルトグループ間で強度差を呈する。Ｓ_２および単原子酸素分子グループのときと同じように、Ｏ_２分子グループは、各アスファルトグループ内で強度に大きな変動を呈する。Ｏ_２分子グループ（４≦ｚ≦２２）の場合、グループＩ、ＩＩおよびＩＩＩのアスファルトは、グループＩＶのアスファルトよりも大きい強度を呈する。
【００２７】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒが単原子窒素置換である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１７種の分子グループを評価する。窒素分子グループの強度と４つのアスファルトグループのレオロジー性能との間には、なんら傾向はみられない。
【００２８】
Ｒ＝ＳＯである式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される５種の高芳香族性分子グループを評価する。５つのグループは全て（１００％）、レオロジー性能ランクの関数として強度を呈する。グループＩ、ＩＩおよびＩＩＩのアスファルトは、Ｒ＝ＳＯかつ（１６≦ｚ≦２０）であるＣ_ｎＨ_{（２ｎ±ｚ）}−Ｒに関しより大きい強度を呈する。グループＩＩＩおよびＩＶのアスファルトは、グループＩおよびＩＩのアスファルトよりも、（２２≦ｚ≦２６）に関しより小さい強度を呈する。
【００２９】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒ＝ＮＯである式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される５種の分子グループを評価する。５種の分子グループは全て（１００％）、４つのアスファルトグループ間で強度差を呈する。グループＩ、ＩＩおよびＩＩＩのアスファルトは、グループＩＶのアスファルトよりも、ＮＯ分子グループ（９≦ｚ≦２１）に関しより大きい強度を呈する。
【００３０】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒ＝Ｏ_３、ＳＯ_２、またはＮＯ_２である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される種々の分子グループを評価する。グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトは、Ｏ_３分子グループでもＮＯ_２分子グループでも強度差を示さない。グループＩおよびＩＩのアスファルトは、第グループＩＩＩおよびＩＶのアスファルトよりも、ＳＯ_２分子グループに関しわずかに大きい強度を呈する。
【００３１】
１１種の異なる原油スレートから得られた３１種の減圧残渣に関しＨＲ／ＭＳフィンガープリントを作成した。レオロジー指数およびレオロジーパラメーターは、図４に示される１０種の原油スレートから得られた２７種の残渣のサブセットで利用可能であった。（ＭＥＮ＝Ｍｅｎｅｍｏｔｏ；ＢＣＦ−２２＝Ｂａｃｈｅｑｕｅｒｏ−２２；ＣＬ＝Ｃｏｌｄ ｌａｋｅ；ＢＲ＝Ｂｏｗ Ｒｉｖｅｒ；ＡＨＦ＝Ａｒａｂｉａｎ Ｈｅａｖｙ／Ｆｏｒｔｉｅｓブレンド）
【００３２】
それぞれの原油スレートの全体的序数型ランクは、その原油スレートから得られた減圧残渣の平均序数型ランクを求めて、その平均の平均値を計算することにより決定した。
【００３３】
それぞれのグループに属するアスファルトの分子組成を調べて４つのグループ間に差異があるかを決定した。この差異は、式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１２０種の分子グループのＨＲ／ＭＳフィンガープリントを用いるレオロジー性能の差異と一致した。グループＩ、ＩＩ、ＩＩＩおよびＩＶアスファルトについて、平均強度および標準偏差を計算した。９５％信頼区間を用いて、グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトで、それぞれの分子グループの強度の範囲を予測した。
【００３４】
それぞれのレオロジーグループの強度、芳香族性、炭素数および分子量の平均値に基づいて、少なくとも１２０種の分子グループのライブラリーを用いて次の関数関係について分子プロフィールをプロットした。
（ａ）強度＝ｆ（分子グループ、芳香族性）
（ｂ）芳香族性＝ｆ（分子グループ、強度）
（ｃ）平均アルキル側鎖長＝ｆ（分子グループ、芳香族性）
（ｄ）平均分子量＝ｆ（分子グループ、芳香族性）
【００３５】
分子プロフィールを比較することにより、良好なアスファルト（グループＩ）と不十分なアスファルト（グループＩＶおよびＶ）と間の分子組成の統計的有意差を明確化した。これに基づいて最適アスファルト組成を規定した。上記の関数関係のそれぞれについて、以下の分子モーメント（曲線下側の一次面積モーメント）を計算する。
（ａ）Ｒｉ＝分子グループＲの強度モーメント
（ｂ）Ｒｚ＝分子グループＲの芳香族性モーメント
（ｃ）Ｒｃ＝分子グループＲの平均アルキル側鎖長モーメント
（ｄ）Ｒｍ＝分子グループＲの平均分子量
【００３６】
グループＩおよびグループＩＶのアスファルトのＨＲ／ＭＳフィンガープリントの差異を図１に例示する。アスファルトは、それらの原料の原油または原油ブレンドに基づき、相対的フィールド性能に関してランクづけすることができる。レオロジーランクづけシステムは、アスファルトが組み込まれた舗道の性能を正確に反映および予測する経験的および機械的アスファルトバインダー試験から得られる性能パラメーターの組み合わせに基づく。レオロジーランクづけシステムにより同定される異なるアスファルトグループ（即ち、グループＩ、ＩＩ、ＩＩＩおよびＩＶ）は、異なる分子組成を呈する。１つのレオロジーグループに属するアスファルトの分子組成は類似している。アスファルトグループ間の分子組成の差異には一貫性がある。アスファルトのレオロジー性能およびフィールド性能は、その分子組成により予測することができる。
【００３７】
アスファルトのレオロジー性能および舗装性能は、有益な性質を有する成分の濃度を最大化し、有害なまたは他の非有益な性質を有する成分の濃度を最小化するアスファルトおよび原料の原油または原油ブレンドを選択することにより最適化することができる。
【００３８】
予備的フィンガープリント測定を行うために、８５／１００領域に針入度を有するＭｅｎｅｍｏｔｏ（ＭＥＮ）、Ｂｏｕｎｄａｒｙ Ｌａｋｅ（ＢＬ）およびＣｏｌｄ Ｌａｋｅ（ＣＬ）アスファルト／減圧残渣のようにアスファルトの製造に利用される典型的な重質原油を選択した。３種のアスファルトは、明確に異なる舗装性能を呈する。最初のＨＲ／ＭＳフィンガープリントは、極性−１留分で作成した。スルホキシド、カルボン酸、フェノールおよびピリジンを、骨材への接着の主要因となる極性官能基として、ＳＨＲＰ Ａ３４１文書に基づいて同定した。
【００３９】
３種の代表的な原油に由来する留分のＨＲ／ＭＳフィンガープリントを図２に示す。反復なし、有意水準データ０．０５で、Ｅｘｃｅｌ ５．０ Ｔｗｏ Ｆａｃｔｏｒ Ａｎａｌｙｓｉｓ ｏｆ Ｖａｒｉａｎｃｅ（ＡＮＯＶＡ）を用いて、データの統計的有意性を分析した。分析の結果、ＨＲ／ＭＳフィンガープリント法により、組み合わせヘテロ原子フラグメントに基づいて０．０５の有意水準で３種のアスファルトを区別しうることが示唆された。ＭＥＮ残渣は、他の２種のアスファルトよりも、評価対象の分子種に関しより大きい強度を呈したことから、より極性の大きい材料であることが示唆された。ＣＬおよびＢＬアスファルトは、硫化物強度の差により区別された。
【００４０】
予備実験の結果から、アスファルトのフィンガープリントが取得可能であることおよび異なる品質のアスファルトが異なる濃度の分子フラグメントを呈することが実証された。特定のフラグメントの有意性またはアスファルト性能へのその寄与率は決定されなかった。
【００４１】
第二世代ＨＲ／ＭＳフィンガープリントは、組み合わせヘテロ原子の拡張物質ライブラリーに基づくものであり、芳香族留分および極性−１留分の両方を含み、評価対象のアスファルトの割合を効果的に５０重量パーセントよりも大きくした。正規型分子フラグメント分布を用いて第二世代ＨＲ／ＭＳフィンガープリントを構築した。単一の針入度グレードまたはＳＵＰＥＲＰＡＶＥ（登録商標） ＰＧグレードに属する全てのアスファルト／残渣のフィンガープリントを評価し、どの官能基が統計的に特有のフィンガープリントを生成するかを決定した。
【００４２】
Ｍｅｎｅｍｏｔａ（ＭＥＮ）、Ｂａｃｈｅｑｕｅｒｏ−２２（ＢＣＦ−２２）およびＣｏｌｄ Ｌａｋｅ（ＣＬ）のように３種の異なる原油から得られた典型的な８５／１００針入度アスファルトのＨＲ／ＭＳフィンガープリントを図３に示す。Ｅｘｃｅｌ ５．０を用いてデータを検査し、異なる原料原油から得られたアスファルト間の統計的有意差が存在するかを確認した。分子種の全ライブラリーを用いたが、原料の異なるアスファルト間の統計的有意差は存在しなかった。第一世代フィンガープリントでうまく行くことが実証された組み合わせヘテロ原子サブセットを用いたが、統計的有意差は存在しなかった。酸素、窒素および組み合わせヘテロ原子基のサブセットを使用したとき、より軟質のアスファルトは統計的有意差を呈し、８５／１００針入度（ＳＵＰＥＲＰＡＶＥ ＰＧ ５８〜２２）アスファルトは、境界線上の差異を呈した。酸素、窒素および組み合わせヘテロ原子官能基が組み込まれたＨＲ／ＭＳフィンガープリントを用いると、改良された組成指数を開発することができる。図４は、質量スペクトルに及ぼす原油の組成変化の影響を示している。
【００４３】
ＨＲ／ＭＳに付す残渣試料は、好ましくは、所定の温度、所与の時間、一定の低圧で、正確に全原油を加熱することのできる装置を用いて調製される。装置は温度条件および減圧条件のいずれに対しても優れた長期間安定性を示すことが重要である。装置の温度および減圧度は変化させうるが、所定の圧力で目標大気圧換算温度（ＡＥＴ）に対応する温度が得られた後は、温度および圧力はいずれも、実験全体にわたって一定に保持される。実験時、周囲圧以下の圧力（減圧）にすると、アスファルト／残渣の熱分解が防止される。アスファルト／残渣を得るために、目標ＡＥＴに対応する正確な温度−圧力の組み合わせを決定することが必要である。ＡＳＴＭ Ｄ５２３６に概要されているようにこれを行うことができるが、その手順では、温度および圧力の両方を正確に測定することが必要である。この手順の実施中に装置の温度を測定することは簡単であるが、作動圧力を測定することは一般に難しい。圧力の直接測定を回避すべく、この方法では、１組の公知の原油の蒸留プロフィールを用いて温度−圧力条件に対して装置を校正する。プロセス温度の読取り値とＡＥＴとの相関は、校正物質原油の蒸留プロフィールを用いて決定される。
【００４４】
好ましい方法では、小型密閉チャンバーに秤量済み凍結原油試料を配置し、メカニカルポンプにより一次的にポンプダウンし、次いで小型密閉チャンバーから少なくとも１Ｌの容積を有する減圧レベル既知（例えば、１ｍＴｏｒｒ）のチャンバーへの通路（即ち、加熱マニホールド）を開放する。中間生成物、残油および経時アスファルトを、原油の代わりに使用するかまたは原油と混合することができる。好ましい試料サイズは１０〜４０ｍｇであるが、２〜２００ｍｇも本発明の一部をなすと見なされる。次に、平衡後に残存する残渣を取り出して再び秤量する。１回目の測定重量と２回目の測定重量の比がＡＥＴ収率となる。減圧チャンバーを連続的にポンプダウンするか、減圧チャンバーを所望の圧力に達した後に閉鎖した後試料に暴露するかに応じて減圧ポンプラインまたは減圧チャンバーから採取したガスを分析することにより、他の情報を決定することができる。
【００４５】
好ましい装置は、試料オーブン、試料ホルダーおよび全ガラス製加熱マニホールドを有する。装置は、１ｍＴｏｒｒ（１０^−３Ｔｏｒｒ）の絶対圧力を達成することができる。試料を石英管ボート中に秤量し、液体窒素浴中で冷却する。次に、それを試料ホルダー中に入れてマニホールドに取り付ける。マニホールド中の高温ガラスバルブを用いて試料を周囲圧以下の圧力に暴露する。他のボートを使用してもよいが、石英が好ましい。試料を減圧に暴露する際、試料オーブンを周囲温度から目標温度まで加熱し、その温度に所定の時間保持する。試料調製時間全体にわたり一定の高温（３００〜３５０℃）に保持されるマニホールドは、試料ホルダーと、装置により生成される減圧との間の物理的インターフェースを可能にする。この方法では、抜頭処理される各原油に対して減圧を発生させたり分配したりする必要はない。これにより、全原油からのアスファルト／残渣の試料調製時間が大幅に削減される。
【００４６】
ＡＥＢＰおよび原油の性質にもよるが、この方法により、５ｍｌの全原油から約２０ｇのアスファルトまたは残渣が生成される。好ましい試料形態は、シート、薄膜および液滴である。これらの試料形態をとれば、試料を急速に冷却または加熱するための十分に大きな表面積が得られる。オーブンの減圧度が高くなるほど（圧力が低くなるほど）、オーブン温度を低くすることができるので、試料の分解を低減させることができる。本発明の好ましい態様では、１５分以下の試料平衡時間、定減圧度緩衝器および０．２％の繰り返し精度を有する固定温度オーブンを使用する。「凍結」という用語は、試料の損傷を引き起こすほどの水の気化が少なくとも３０〜６０秒間起こらないように、十分に低い温度まで冷却することを意味する。
【図面の簡単な説明】
【図１】
グループＩ〜ＩＶのアスファルトのフィンガープリントスペクトル（強度ｖｓ質量）を示している。
【図２】
３種の代表的な原油（ＭＥＮ、ＣＬおよびＢＬ）に由来する留分のフィンガープリントスペクトル（強度ｖｓ質量）を示している。
【図３】
３種の代表的な原油（ＭＥＮ、ＢＣＦ−２２およびＣＬ）から得られたアスファルトのフィンガープリントスペクトル（強度ｖｓ質量）を示している。
【図４】
グループＩ〜Ｖのレオロジーグループ（ＲＧ）について、炭素数、分子量および強度ｖｓ質量を示している。[0001]
This application claims priority from US Provisional Patent Applications Nos. 60 / 258,900, 60 / 256,129 and 60 / 258,899, all filed on December 15, 2000. Insist.
[0002]
Background of the Invention
Multivariate models include component concentrations such as benzene content, saturated compound content, aromatics content and olefin content in automotive gasoline, diesel fuel, jet fuel and process streams, gasoline research and motor octane numbers, and diesel fuel. This is a basic model for estimating properties such as cetane number from an infrared spectrum using an online infrared analyzer. For example, Maggard describes the use of a multivariate model to determine the content of paraffins, isoparaffins, aromatics, naphthenes and olefins in motor gasoline and gasoline components (US Pat. No. 5,349,189). . Maggard also describes the use of MLR to measure octane and cetane numbers (US Pat. No. 4,963,745 and US Pat. No. 5,349,188). Perry and Brown (U.S. Pat. No. 5,817,517) describes the use of FT-IR to determine the composition of feeds that are sent to hydrocarbon conversion, separation and blending processes.
[0003]
The use of multivariate models is not limited to infrared analyzers. Jaffe describes the use of gas chromatography to estimate the octane number of gasoline (US Pat. No. 4,251,870). Ashe, Roussis, Fedora, Felsky and Fitzgerald describe the use of gas chromatography / mass spectrometry (GC / MS) and multivariate modeling to predict the chemical or physical properties of crude oil (US Pat. No. 5). 699, 269). Cooper, Bledsoe, Wise, Sumner and Welch describe the use of Raman spectroscopy and multivariate modeling to estimate gasoline octane number and Reid vapor pressure (US Pat. No. 5,892,228).
[0004]
Conventional asphalt binder specifications address binder properties such as penetration, viscosity, ductility, softening point, etc., which have a history of empirical correlation with asphalt pavement performance during use. SUPERPAVE (R) for rheologically simple asphalt binders based on rheological performance under limited frequency and temperature conditions, because standards based on conventional properties have failed to provide stable and durable road surfaces. (Registered trademark) standard has been developed. The SUPERPAVE® standard does not currently address rheologically complex materials, and currently does not distinguish the performance of asphalt with the same performance grade (PG).
[0005]
Attempts to rank molecular components based on conventional and SUPERPAVE® type performance parameters to identify “ideal” asphalt compositions have been unsuccessful. Using a single performance parameter to rank the performance of each asphalt or vacuum residue masks the relationship between composition and performance. The rank assigned depends on which parameter is selected (ie, penetration at 25 ° C., SUPERPAVE width between PG temperatures (Tmax and Tmin), G at Tg). ^* Etc.) and changes greatly. The assigned rank has also been found to be too sensitive to the distillation cut temperature of the residue.
[0006]
It would be beneficial to find a way to rank and identify an acceptable or ideal asphalt composition by testing the feedstock or blend under consideration prior to asphalt production.
[0007]
Summary of the Invention
According to the present invention, a combination of conventional and rheological parameters provides a composite rheological rank that accurately predicts the relative field performance of asphalt. When this rank is used, rheologically similar asphalt and vacuum residues preferably have a commonality in molecular composition as determined by high resolution mass spectrometry. A higher abundance of a particular molecular structure indicates better asphalt pavement performance.
[0008]
Detailed description of the invention
A method was developed to rapidly predict and improve the asphalt quality of unknown crude oil. To achieve that goal, a clear relationship between molecular composition and asphalt pavement performance is required. High resolution mass spectrometry (HR / MS) was used to establish a relationship between crude slate and asphalt molecular composition independent of penetration and performance grade. Formula C _n H _{(2n ± z)} A molecular structure represented by -R, wherein n is generally greater than 10, z is from 0 to about 44, and R is a heteroatom or a combination of heteroatoms containing sulfur, nitrogen or oxygen. , About 120 molecular groups were identified. Molecular groups are used to distinguish asphalt from different crude slate and are not significantly affected by the distillation cut temperature of the residue from the same crude slate. The link between asphalt composition and pavement performance is determined by empirical (by standards) and mechanical (rheological) measurements on asphalt binders in the laboratory.
[0009]
The present invention is a method for determining the suitability of crude oil, a mixture of different crude oils (crude oil slate) and a crude oil fraction as a raw material for asphalt production based on the chemical concentrations of several HR / MS molecular fragments in the raw material sample. is there. Certain fingerprint areas contain individual molecular components that are expected to function properly in the asphalt.
[0010]
The determination of the optimal asphalt composition from the molecular moment is preferably
a) selecting asphalt or residue;
b) performing a conventional test, a SUPERPAVE® test and / or a rheological test;
c) determining the rheological index of the sample;
d) determining the average rheological index (RI ′) of the crude slate;
e) assigning a rheology group (RG, eg groups I-IV);
f) calculating average strength, aromaticity, carbon number and molecular weight for each RG;
g) For each molecular group (hydrocarbon, sulfur, oxygen, etc.), plot the average of Z = f (I), I = f (Z), MW = f (Z), C # = f (Z) Performing the step;
h) The molecular moment is calculated by the following formula:
Molecular moment = sum of (strength x aromaticity) / sum of (aromaticity)
Calculating by;
i) comparing the molecular profiles of good asphalt (Group I) and poor asphalt (Group IV); and
j) Step of confirming statistical significance of difference using molecular moment
Is achieved by a method including:
[0011]
The prediction of asphalt performance from the molecular composition is preferably
a) selecting asphalt or residue;
b) performing high resolution mass spectrometry;
c) calculating the average of Z = f (I), I = f (Z), MW = f (Z), C # = f (Z) for each molecule group;
d) determining the expected rheological index (RI) of the sample using the formula RI = f (moment);
e) comparing the predicted RI to the RI of good asphalt (Group I) and poor asphalt (Group IV);
f) determining the rheological group of the sample;
g) predicting the suitability of the crude slate for asphalt production based on RG; and
h) confirming the suitability of the crude slate for asphalt production by comparing it with Group I and Group IV asphalt
Is achieved by a method including:
[0012]
A mathematical description of a preferred model for determining the rheology index (RI) in step (d) above is as follows.
RI = 13.863-1.118964E-1 ^* Hc + 6.12843E-2Hi-4.1153E-1Hz-4.68191E-3Ni + 6.655557E-3Oi + 5.88057E-3Sm-1.42995E-1Sz-3.14998E-3 [C5ARings-]-3.35754E-3 [C5ARings +] (Where R ² = 0.95).
[0013]
The following molecular moment characteristics are preferred for asphalt production. Asphalts for paving exhibiting good performance generally have higher strength of hydrocarbon molecular groups of 10 ≦ z ≦ 26, lower strength of hydrocarbon molecular groups of 28 ≦ z ≦ 44, and 12 ≦ z ≦ 22, the strength of the highly aromatic sulfur molecule group of 24 ≦ z ≦ 34 is lower, the formula C _n H _{(2n ± z)} R = S at -R ₂ Is a highly aromatic S ₂ The strength of the molecular group (14 ≦ x ≦ 20) is smaller, _n H _{(2n ± z)} In the group -R, the oxygen molecule group in which R is a monoatomic oxygen substitution (12 ≦ z ≦ 20) and the oxygen atom group with a high aromaticity (22 ≦ z ≦ 32) are stronger, and the molecular group in which z> 32 Has no difference in strength between asphalts. C where 4 ≦ z ≦ 22 _n H _{(2n ± z)} = O ₂ For the molecular group, good and medium asphalts exhibit greater strength than poor asphalts. C _n H _{(2n ± z)} For = SO, good asphalt exhibits greater strength when 16 ≦ z ≦ 26. C _n H _{(2n ± z)} For = NO, good asphalt exhibits greater strength than poor asphalt when 9 ≦ z ≦ 21. SO ₂ For the molecular group, good asphalt exhibits slightly greater strength than poor asphalt. FIG. 4 shows a comparison of these types.
[0014]
In the present invention, three classes of performance parameters are used to rank asphalt and vacuum residue and predict their pavement performance.
I. Conventional parameters: may include properties and specifications such as penetration, viscosity, softening point, ductility, Canadian General Standards Board (CGSB) grade, Fraass point, n-heptane insolubles, elemental analysis, and the like.
II. SUPERPAVE® performance parameters: performance grade (PG XX-YY), SUPERPAVE® width (numeric difference between high and low specification temperatures XX and YY), crossover temperature (Tmax, Tmin, and Tfat; specification) And a crossover temperature width (Tmax−Tmin).
III. Rheological index obtained from complete rheological analysis within the linear viscoelastic region of the material: SHRP rheological model (master curve index Gg, η0, ωc and Tref = R at + 10 ° C.) and phase response index (Tf, Tb, T45 ＠ δ = 10 rad / s isochronous curve), black diagram characteristics, and the like.
[0015]
Conventional asphalt properties, CGSB grades, SUPERPAVE® performance parameters and rheology indices all describe the temperature sensitivity of asphalt in terms of load carrying capacity, deformability, strain resistance and deformation recovery after unloading. Used for purposes. Each parameter measures various aspects of the material response. In the present invention, a method of combining parameters was developed to completely describe the behavior of asphalt as a function of crude slate, independent of the distillation cut temperature.
[0016]
By an iterative process, the parameters as shown in Table 1 were selected to rank the asphalt and vacuum distillation residue for pavement performance. Because the majority of these parameters are based on classical rheology, they are called rheological performance parameters.
[0017]
An ordinal or regular nominal ranking system is used for the parameters as shown in Table 1, based on values that optimize pavement performance in general applications. Performance parameters are measured or calculated for each vacuum residue obtained from a given crude slate at a given cut temperature. A rank for each parameter is assigned to the residue based on the parameter-by-parameter comparison. If the parameters are equivalent or identical, duplicate ranks are allowed. An average rank of the residue is calculated based on the rank of the individual parameters. The overall rank of each crude slate is determined by calculating the average of the average ranks determined for all the residues obtained from the crude slate in the previous step (FIG. 1). Based on the rheology rank, five rheological “quality” groups of paving asphalt are identified. Group I is "good" asphalt, Group II is "good" asphalt, Group III is "satisfactory" asphalt, and Groups IV and V are "poor" and "very poor". It is asphalt.
[0018]
The molecular composition of asphalt belonging to each group is represented by the formula C _n H _{(2n ± z)} Using HR / MS fingerprints of 120 molecular groups denoted by -R is consistent with rheological performance. FIG. 3 shows an example of how different crudes produce asphalts of different compositions.
[0019]
The average strength and standard deviation were calculated for asphalts of Groups I, II, III and IV.
[0020]
[Table 1]

[0021]
Formula C _n H _{(2n ± z)} The HR / MS fingerprint of the vacuum residue obtained from a crude slate of unknown performance is generated using the 120 molecular groups denoted by -R.
[0022]
Formula C _n H _{(2n ± z)} Evaluate 24 types of hydrocarbon molecule groups represented by Seventeen of the molecular groups (71% of the total) exhibit intensity differences as a function of asphalt rheology rank. Group I, II, III and IV asphalts show no difference in intensity with respect to low aromatic hydrocarbon molecular groups (z ≦ 8). Group IV asphalts generally exhibit less strength for moderately aromatic groups of hydrocarbon molecules (10 ≦ z ≦ 26) than Group I, II or III asphalts. Group IV asphalt generally exhibits greater strength with respect to highly aromatic hydrocarbon molecular groups (28 ≦ z ≦ 44) than Group I, II or III asphalts.
[0023]
For asphalts of groups I, II, III and IV, formula C wherein R is a single sulfur substitution _n H _{(2n ± z)} Evaluate the 19 molecular groups denoted by -R. Ten of the molecular groups (53% of the total) exhibit intensity differences between the four asphalt groups. Group I, II, III and IV asphalts show no difference in intensity with low aromatic sulfur molecular groups (z ≦ 10). Group III and Group IV asphalts generally exhibit less strength with respect to moderately aromatic sulfur molecular groups (12 ≦ z ≦ 22) than Group I and Group II asphalts. Group IV asphalt generally exhibits greater strength with respect to highly aromatic sulfur molecular groups (24 ≦ z ≦ 34) than Group I, II or III asphalts.
[0024]
Group I, II, III and IV asphalt, R = S ₂ Expression C which is _n H _{(2n ± z)} Evaluate 10 molecular groups denoted by -R. Three of the ten molecular groups (30% of the total) exhibit intensity differences between the four asphalt groups. It must be noted that the data exhibits large fluctuations. In general, Group IV asphalts have higher aromatic S than group I, II or III asphalts. ₂ It exhibits greater intensity for the molecular groups (14 ≦ x ≦ 20).
[0025]
For asphalts of groups I, II, III and IV, formula C wherein R is a monoatomic oxygen substitution _n H _{(2n ± z)} Evaluate the 20 molecular groups denoted by -R. Twelve of the twenty molecular groups (60% of the total) exhibit intensity differences between the four asphalt groups. As with the disulfide molecular groups, the oxygen molecular groups exhibit large variations in intensity within each asphalt group. Group I, II, III and IV asphalts show no difference in intensity for the low aromatic oxygen molecular groups (z ≦ 10). Group IV asphalts exhibit less strength for moderately aromatic oxygen molecular groups (12 ≦ z ≦ 20) than Group I, II and III asphalts. Group III and IV asphalts exhibit lower strength for highly aromatic oxygen molecular groups (22 ≦ z ≦ 32) than Group I or II asphalts. In the case of the molecular group where z> 32, there is no difference in intensity between the four asphalt groups.
[0026]
For asphalts of Groups I, II, III and IV, R = O ₂ Expression C which is _n H _{(2n ± z)} Evaluate the 14 molecular groups denoted by -R. Twelve (85.7%) of the twenty molecular groups exhibit intensity differences between the four asphalt groups. S ₂ And as in the monoatomic oxygen group, ₂ The molecular groups show large variations in intensity within each asphalt group. O ₂ For the molecular groups (4 ≦ z ≦ 22), the asphalts of groups I, II and III exhibit greater strength than the asphalts of group IV.
[0027]
For asphalts of groups I, II, III and IV, the formula C wherein R is a monoatomic nitrogen substitution _n H _{(2n ± z)} Evaluate the 17 molecular groups denoted by -R. There is no trend between the strength of the nitrogen molecule group and the rheological performance of the four asphalt groups.
[0028]
Formula C where R = SO _n H _{(2n ± z)} The five highly aromatic groups represented by -R are evaluated. All five groups (100%) exhibit strength as a function of rheological performance rank. Group I, II and III asphalts have C = R and R = SO and (16 ≦ z ≦ 20) _n H _{(2n ± z)} It exhibits greater strength with respect to -R. Group III and IV asphalts exhibit less strength with respect to (22 ≦ z ≦ 26) than Group I and II asphalts.
[0029]
For asphalts of groups I, II, III and IV, formula C wherein R = NO _n H _{(2n ± z)} Evaluate the five molecular groups denoted by -R. All five molecular groups (100%) exhibit intensity differences between the four asphalt groups. Group I, II and III asphalts exhibit greater strength with respect to NO molecular groups (9 ≦ z ≦ 21) than group IV asphalts.
[0030]
For asphalts of Groups I, II, III and IV, R = O ₃ , SO ₂ Or NO ₂ Expression C which is _n H _{(2n ± z)} Evaluate various molecular groups denoted by -R. Group I, II, III and IV asphalts are ₃ NO in molecular group ₂ Even the molecular groups show no difference in intensity. Group I and II asphalts have a higher SO than group III and IV asphalts. ₂ It exhibits slightly greater intensity for the molecular groups.
[0031]
HR / MS fingerprints were generated for 31 vacuum residues obtained from 11 different crude slate. The rheology index and rheology parameters were available for a subset of the 27 residues obtained from the 10 crude slate shown in FIG. (MEN = Menemoto; BCF-22 = Bachequero-22; CL = Cold lake; BR = Bow River; AHF = Arabian Heavy / Forties blend)
[0032]
The overall ordinal rank of each crude slate was determined by determining the average ordinal rank of the vacuum residue obtained from that crude slate and calculating the average of the averages.
[0033]
The molecular composition of the asphalts belonging to each group was examined to determine if there was a difference between the four groups. This difference is given by the formula C _n H _{(2n ± z)} Consistent with the difference in rheological performance using the HR / MS fingerprint of the 120 molecular groups denoted by -R. Average strength and standard deviation were calculated for Groups I, II, III and IV asphalt. A 95% confidence interval was used to predict the range of intensities of each molecular group on asphalts of Groups I, II, III and IV.
[0034]
Based on the average value of intensity, aromaticity, carbon number and molecular weight of each rheological group, molecular profiles were plotted using a library of at least 120 molecular groups for the following functional relationships:
(A) Strength = f (molecular group, aromaticity)
(B) Aromaticity = f (molecular group, strength)
(C) average alkyl side chain length = f (molecular group, aromaticity)
(D) average molecular weight = f (molecular group, aromaticity)
[0035]
Comparing the molecular profiles revealed a statistically significant difference in molecular composition between good asphalt (Group I) and poor asphalt (Groups IV and V). Based on this, the optimum asphalt composition was defined. For each of the above functional relationships, the following molecular moment (primary area moment under the curve) is calculated.
(A) Ri = intensity moment of molecule group R
(B) Rz = aromatic moment of molecular group R
(C) Rc = average alkyl side chain length moment of molecular group R
(D) Rm = average molecular weight of molecular group R
[0036]
The differences in HR / MS fingerprints of Group I and Group IV asphalts are illustrated in FIG. Asphalt can be ranked for relative field performance based on the crude or crude blend of those feeds. The rheology ranking system is based on a combination of performance parameters derived from empirical and mechanical asphalt binder tests that accurately reflect and predict the performance of asphalt-incorporated pavements. The different asphalt groups identified by the rheology ranking system (ie, groups I, II, III and IV) exhibit different molecular compositions. The molecular composition of asphalts belonging to one rheological group is similar. The differences in molecular composition between asphalt groups are consistent. The rheological and field performance of asphalt can be predicted by its molecular composition.
[0037]
Asphalt rheological and pavement performance selects asphalt and raw crude or crude blends that maximize the concentration of components with beneficial properties and minimize the concentration of components with harmful or other non-beneficial properties Can be optimized.
[0038]
Used for the production of asphalt like Menemoto (MEN), Boundary Lake (BL) and Cold Lake (CL) asphalt / vacuum residue with penetration in 85/100 area to make preliminary fingerprint measurements A typical heavy crude was selected. The three asphalts exhibit distinctly different pavement performances. The first HR / MS fingerprint was made with the polar-1 fraction. Sulfoxides, carboxylic acids, phenols, and pyridines were identified based on the SHRP A341 document as polar functional groups that are the main contributors to aggregate adhesion.
[0039]
The HR / MS fingerprints of the fractions from three representative crudes are shown in FIG. Data were analyzed for statistical significance using Excel 5.0 Two Factor Analysis of Variance (ANOVA) with no repetition and significance level data of 0.05. Analysis indicated that HR / MS fingerprinting could distinguish the three asphalts at a significance level of 0.05 based on the combined heteroatom fragments. The MEN residue exhibited greater strength with respect to the molecular species being evaluated than the other two asphalts, indicating that it was a more polar material. CL and BL asphalts were distinguished by differences in sulfide strength.
[0040]
Preliminary experiments have demonstrated that asphalt fingerprints are obtainable and that different quality asphalts exhibit different concentrations of molecular fragments. The significance of a particular fragment or its contribution to asphalt performance was not determined.
[0041]
The second generation HR / MS fingerprint is based on an extended substance library of combinatorial heteroatoms and includes both aromatic and polar-1 fractions, effectively reducing the proportion of asphalt to be evaluated by 50%. Greater than weight percent. A second generation HR / MS fingerprint was constructed using the canonical molecular fragment distribution. All asphalt / residue fingerprints belonging to a single penetration grade or SUPERPAVE® PG grade were evaluated to determine which functional groups produced a statistically unique fingerprint.
[0042]
HR / MS fingerprints of typical 85/100 penetration asphalt obtained from three different crudes such as Menemoto (MEN), Baquequero-22 (BCF-22) and Cold Lake (CL) are shown in FIG. Shown in The data was examined using Excel 5.0 to determine if there was a statistically significant difference between asphalt obtained from different feed crudes. Using the entire library of molecular species, there was no statistically significant difference between the different asphalt raw materials. Combinatorial heteroatom subsets demonstrated to work well with first generation fingerprints were used, but there were no statistically significant differences. When using a subset of oxygen, nitrogen and combined heteroatom groups, the softer asphalt exhibited statistical significance and the 85/100 penetration (SUPERPAVE PG 58-22) asphalt exhibited borderline differences. . With HR / MS fingerprints incorporating oxygen, nitrogen and combined heteroatom functionality, an improved composition index can be developed. FIG. 4 shows the effect of a change in crude oil composition on the mass spectrum.
[0043]
The residue sample to be subjected to HR / MS is preferably prepared using a device capable of accurately heating whole crude oil at a given temperature for a given time at a constant low pressure. It is important that the device exhibit excellent long-term stability under both temperature and reduced pressure conditions. Although the temperature and the degree of pressure reduction of the apparatus can be changed, after the temperature corresponding to the target atmospheric pressure conversion temperature (AET) is obtained at a predetermined pressure, both the temperature and the pressure are kept constant throughout the experiment. . During the experiment, if the pressure is lower than the ambient pressure (reduced pressure), thermal decomposition of asphalt / residue is prevented. In order to obtain asphalt / residue, it is necessary to determine the exact temperature-pressure combination corresponding to the target AET. This can be done as outlined in ASTM D5236, but the procedure requires accurate measurements of both temperature and pressure. Measuring the temperature of the device during the performance of this procedure is straightforward, but measuring the operating pressure is generally difficult. To avoid direct pressure measurements, the method uses a set of known crude oil distillation profiles to calibrate the equipment for temperature-pressure conditions. The correlation between the process temperature reading and the AET is determined using the distillation profile of the calibrator crude oil.
[0044]
In a preferred method, a weighed frozen crude sample is placed in a small sealed chamber, pumped down temporarily by a mechanical pump, and then transferred from the small sealed chamber to a chamber of known vacuum level (eg, 1 mTorr) having a volume of at least 1 L. Open the passage (ie, the heating manifold). Intermediates, resids and aged asphalt can be used in place of crude oil or mixed with crude oil. The preferred sample size is 10-40 mg, but 2-200 mg is also considered to be part of the present invention. Next, the residue remaining after equilibration is taken out and weighed again. The ratio of the first measured weight to the second measured weight is the AET yield. By analyzing the gas taken from the vacuum pump line or vacuum chamber, depending on whether the vacuum chamber is continuously pumped down or the vacuum chamber is closed after reaching the desired pressure and then exposed to the sample, Information can be determined.
[0045]
A preferred device has a sample oven, a sample holder and an all glass heating manifold. The device is 1 mTorr (10 ^-3 Torr) absolute pressure can be achieved. The sample is weighed into a quartz tube boat and cooled in a liquid nitrogen bath. Next, it is placed in the sample holder and attached to the manifold. The sample is exposed to sub-ambient pressure using a hot glass bulb in the manifold. Other boats may be used, but quartz is preferred. When exposing the sample to reduced pressure, the sample oven is heated from ambient temperature to a target temperature and held at that temperature for a predetermined time. The manifold, which is held at a constant high temperature (300-350 ° C.) throughout the sample preparation time, allows a physical interface between the sample holder and the reduced pressure generated by the device. In this way, there is no need to create or distribute a vacuum for each crude to be decapitated. This greatly reduces asphalt / residue sample preparation time from whole crude oil.
[0046]
Depending on the nature of the AEBP and the crude, this method produces about 20 g of asphalt or residue from 5 ml of total crude. Preferred sample forms are sheets, thin films and droplets. These sample forms provide a sufficiently large surface area to rapidly cool or heat the sample. The higher the degree of decompression of the oven (the lower the pressure), the lower the oven temperature, so that the decomposition of the sample can be reduced. In a preferred embodiment of the present invention, a fixed temperature oven with a sample equilibration time of 15 minutes or less, a constant vacuum buffer and a repeatability of 0.2% is used. The term "freeze" means cooling to a sufficiently low temperature so that water vaporization that does not cause damage to the sample occurs for at least 30-60 seconds.
[Brief description of the drawings]
FIG.
4 shows fingerprint spectra (intensity vs. mass) of asphalts of Groups I to IV.
FIG. 2
Figure 3 shows fingerprint spectra (intensity vs mass) of fractions from three representative crudes (MEN, CL and BL).
FIG. 3
Figure 3 shows asphalt fingerprint spectra (intensity vs. mass) obtained from three representative crudes (MEN, BCF-22 and CL).
FIG. 4
For the rheology groups (RG) of groups IV, the number of carbon atoms, molecular weight and intensity vs. mass are shown.

Claims (14)

A method for selecting crude oil as a raw material for asphalt,
Analyzing the asphalt or a fraction thereof with a high resolution mass spectrometer to produce at least a portion of a mass spectrum;
Comparing at least a portion of said mass spectrum to a database of mass spectral properties;
Determining a class of components or chemical properties from at least one of the similarities and / or differences between the mass spectra; and outputting a result indicating the suitability of the crude oil or crude oil fraction for use as asphalt for an application. A method for selecting crude oil, comprising the step of: A method for selecting crude oil or crude oil residue as a raw material for asphalt,
a) select crude oil or crude oil residue,
Producing asphalt from the crude oil or crude oil residue,
Subjecting the asphalt sample to a rheological test to determine a rheological index of the sample;
By repeating the rheological test and averaging the rheological index, the average rheological index of the crude slate is determined,
Assigning a rheology group to the average rheology index,
For each of the rheology groups, calculate the average strength, aromaticity, carbon number and molecular weight,
Each of the molecular moments is represented by the following formula:
Molecular moment = calculated by the sum of (strength × aromaticity) / (aromaticity),
Compare the molecular profiles of the rheology groups of good asphalt and poor asphalt,
Determining the optimal asphalt composition from the molecular moments by the procedure of using the molecular moments to confirm the statistical significance of the differences; and b) selecting crude oil or crude oil residues;
Subjecting the sample to high resolution mass spectrometry to determine multiple molecular groups,
Calculate the average value for each molecule group,
Determining a predicted rheological index of the sample;
Comparing the predicted rheological index with the rheological index of good asphalt and poor asphalt;
Determining a rheological group of the sample;
Predicting the fitness of crude slate for asphalt production based on the rheology group,
Predicting the asphalt performance of the crude oil or the crude oil residue from the molecular composition by a procedure for confirming the suitability of the crude slate for asphalt production as compared to a rheological group of good asphalt and poor asphalt. A method for selecting crude oil or crude oil residue. The rheology index (RI) is calculated by the following formula:
RI = 13.863-1.11864E-1 ^* Hc + 6.12843E-2Hi-4.1153E-1Hz-4.68191E-3Ni + 6.655557E-3Oi + 5.88057E-3Sm-1.42995E-1Sz-3.14998E-3 [ C5ARings -] - 3.35754E-3 [ C5ARings +] ( wherein ^a R 2 = 0.95)
3. The method for selecting a crude oil or a crude oil residue according to claim 2, which is calculated from the following. The method according to claim 1, wherein the average value is obtained by multiple linear regression analysis, principal component regression analysis, partial least squares regression analysis, or conditional main spectrum analysis. The method of claim 1, wherein the crude is blended. The crude residue is
Cooling the crude oil sample to an average temperature of −200 to 0 ° C .;
Placing the cooled sample in a chamber such that the shape of the sample is small or thin enough to reach equilibrium within 15 minutes with the temperature in the chamber, wherein the chamber comprises 10 minutes. ^{A process} having an absolute pressure of ⁻³ to 10 ⁻⁶ Torr and a fixed temperature of 340 to 540 ° C., so that the combination of the absolute pressure and the fixed temperature is equivalent to the atmospheric pressure equivalent boiling point of the residue to be produced. And holding the sample in the chamber at the absolute pressure and the fixed temperature for 5 to 60 minutes until essentially only the residue remains in the sample. The method for selecting a crude oil according to claim 1, wherein the crude oil is selected. The asphalt is
Cooling the crude oil sample to an average temperature of −200 to 0 ° C .;
Placing the cooled sample in a chamber such that the shape of the sample is small or thin enough to reach equilibrium within 15 minutes with the temperature in the chamber, wherein the chamber comprises 10 minutes. ^{It has} an absolute pressure of ^-3 to 10 ^-6 Torr and a fixed temperature of 340 to 540 ° C, so that the combination of the absolute pressure and the fixed temperature is equivalent to the boiling point of the produced residue in terms of the atmospheric pressure. And holding the sample in the chamber at the absolute pressure and the fixed temperature for 5 to 60 minutes until essentially only residues remain in the sample. 2. The method for selecting crude oil according to claim 1, wherein the crude oil is first produced as a residue sample. The method for selecting a crude oil according to claim 1, wherein at least one selected from the group consisting of an isochronous curve, a master curve, and a black diagram for representing a viscoelastic behavior is measured by the rheological test. . The rheological test measures at least one item selected from the group consisting of a viscosity at 135 ° C, a SUPERPAVE PG temperature range (Tmax-Tmin), and a penetration at 25 ° C. Crude oil selection method. A method for predicting the potential quality of asphalt obtained from crude oil or a blend of crude oils of different origins, comprising:
Using detailed molecular composition and structural data obtained by high-resolution mass spectrometry, and using the following formula:
C _n H _{(2n ± z)} -R
(Where n may be equal to 0, but is usually an integer greater than 10, z is an integer from -4 to +44, R is a heteroatom or a combination of heteroatoms, usually sulfur, nitrogen , Oxygen or combinations thereof, or other heteroatoms, but may not)
Calculating a molecular moment consisting of strength, aromaticity, alkyl side chain length and molecular weight using a molecular library consisting of at least 100 kinds of molecular species represented by:
Associating the molecular moment with a global performance parameter that includes a measurement of rheology-related performance; and associating the global performance parameter with the actual pavement performance of asphalt produced from crude oil or a crude oil blend. A method of predicting the potential quality of a feature. The sample is
Sampling asphalt;
Separating a fraction of asphalt sample based on solubility class, functional group, molecular size or polarity or by other separation techniques; and removing crude oil residue by conventional or non-conventional distillation or whole crude oil decanting techniques 11. The potential of claim 10, comprising a step of producing, wherein each of the steps is produced by a method that can be performed on a crude oil or crude oil blend whose components and proportions are known or unknown. Quality prediction method. The comprehensive performance parameter is at least one item selected from the group consisting of conventional asphalt property scales, and is a group consisting of viscosity at 135 ° C, SUPERPAVE PG temperature range (Tmax-Tmin), and penetration at 25 ° C. The method for predicting potential quality according to claim 10, wherein the calculation can be performed by mathematically combining with at least one item selected. The validity of the comprehensive performance parameter is:
Calculating an average of the global performance parameters from individual values of the global performance parameters of all samples belonging to one crude oil slate;
Ranking the crude slate with respect to other crude slate according to the average of the global performance parameters; and, based on the average performance, assigning the crude rank to the field performance of the asphalt pavement incorporating the crude or crude blend. The method for predicting potential quality according to claim 10, wherein the method is tested by a method including a step of comparing with the potential quality. Crude slate with respect molecular structure represented by the formula _{C n H (2n ± z)} -R,
A hydrocarbon molecule group of 10 ≦ z ≦ 26,
12 ≦ z ≦ 22 sulfur molecule groups,
12 ≦ z ≦ 20 and highly aromatic monoatomic oxygen molecule group,
An oxygen molecule group of 22 ≦ z ≦ 32,
High aromaticity _{S 2} molecule group of 14 ≦ x ≦ 20,
A dioxygen molecule group of 4 ≦ z ≦ 22,
SO molecular group of 16 ≦ z ≦ 26,
Most maximization of the mass intensity of the NO molecular group with 9 ≦ z ≦ 21 and the SO ₂ molecular group;
Minimizing most of the mass intensities of the hydrocarbon molecular groups of 28 ≦ z ≦ 44 and the highly aromatic sulfur molecular groups of 24 ≦ z ≦ 34; and making no distinction for molecular groups of z> 32. The method according to claim 10, wherein the selection is performed based on the potential quality.

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